Methods and compositions for determining severity of heart failure in a subject

ABSTRACT

The application provides a method of determining a severity of heart failure in a human test subject, by determining a level of RNA encoded by one or more heart failure marker genes in blood of the test subject compared to controls.

FIELD OF THE DISCLOSURE

The disclosure relates to methods, kits and compositions for determining the likelihood and/or severity of a subject with heart failure. More particularly, the disclosure relates to methods, kits and compositions for determining the likelihood and/or severity of heart failure by measuring a level of one or more gene products in blood of the subject.

BACKGROUND OF THE DISCLOSURE

Heart failure is increasing as a public health concern and rapidly growing as an economic burden. The enormous public health and economic burdens imposed by heart failure can be decreased only by introducing improved therapies and better patient management. The genomic approaches to disease that have revolutionized biologic and biomedical research over the past 10 years hold significant promise in tackling these issues.

Determining Heart Failure (HF) severity is challenging. New York Heart Association (NYHA) classification and BNP are often used but are limited. Blood gene expression patterns may provide further insights into disease severity, but patterns associated with NYHA class and BNP are unknown.

SUMMARY OF THE DISCLOSURE

The present disclosure provides novel blood markers for determining the likelihood and/or severity of heart failure in a subject. This use can be effected in a variety of ways as further described and exemplified herein.

Accordingly, in one aspect there is provided a method of determining a severity of heart failure in a human test subject, the method comprising, for each gene of a set of one or more of the genes listed in Tables 3, 4, 5, 6, 7 and 8: a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating a test data; b) providing a first positive control data representing levels of RNA encoded by the gene in blood of human control subjects having a first categorized severity of heart failure; and c) comparing the data of steps a) and b) to thereby determine at least one value indicating whether the test data corresponds to the first positive control data; wherein an indication by the at least one value, for each gene of the set, that the test data corresponds to the first positive control data indicates that the test subject has the first categorized severity of heart failure.

In one embodiment, the one or more genes are selected from Tables 3 and 4. In another embodiment, the genes are selected from Tables 5 and 7. The first categorized severity may be compensated heart failure, optionally NYHA I-II heart failure, or decompensated heart failure, optionally NYHA III-IV heart failure.

In a further aspect, the method further comprises providing a second positive control data representing levels of RNA encoded by the gene in blood of human control subjects having a second categorized severity of heart failure, wherein correspondence between the test data and the second positive control data indicates that the test subject has the second categorized severity of heart failure. In one embodiment, the first categorized severity is compensated heart failure, optionally NYHA I-II heart failure and the second categorized severity is decompensated heart failure, optionally NYHA III-IV heart failure.

According to further features described below the determining of the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by the gene in blood of a test subject not having heart failure.

In another aspect, the method further comprises determining levels of RNA encoded by the gene in blood of a population of human subjects having the first categorized severity of heart failure, thereby providing the positive control data representing the levels of RNA encoded by the gene in blood of human control subjects having the first categorized severity of heart failure. In yet another aspect, the method further comprises determining levels of RNA encoded by the gene in blood of a population of human subjects having the second categorized severity of heart failure, thereby providing the positive control data representing the levels of RNA encoded by the gene in blood of human control subjects having the second categorized severity of heart failure.

In a further aspect the method further comprises providing a third control data representing levels of RNA encoded by the gene in blood of human control subjects not having heart failure, and wherein step c) is effected by comparing the test data to the first positive control data, and optionally the second positive control data, and the third control data, wherein correspondence between the test data and the first or second positive control data and not the third control data indicates that the test subject has the first or second categorized severity of heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare the test data to the control data to thereby generate the at least one value indicating whether the test data corresponds to the control data.

According to another aspect, there is provided a computer-based method of determining a severity of heart failure in a human test subject, the method comprising, for each gene of a set of one or more of the genes listed in Tables 3, 4, 5, 6, 7 and 8: inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the test subject, wherein the computer is suitably programmed for comparing a data representing a level of RNA encoded by the gene in blood of a human subject to a control data representing levels of RNA encoded by the gene in blood of human subjects having a categorized severity of heart failure, to thereby output/generate at least one value indicating whether the test data corresponds to the first positive control data; and causing the computer to compare the test data to the first positive control data, wherein an indication by the at least one value that the test data corresponds to the first positive control data indicates that the test subject has the first categorized severity of heart failure.

In one embodiment, the one or more genes are selected from Tables 5 and 7.

In a further aspect, there is provided a method of monitoring the progression of heart failure in a human subject, the method comprising for each gene of a set of one or more of the genes listed in Table 5: a) determining a level of RNA encoded by the gene in blood of the subject at a first time point; b) determining a level of RNA encoded by the gene in blood of the subject at a second time point, wherein the second time point is later than the first time point; and c) comparing the levels of steps a) and b) to thereby determine at least one value indicating whether the level at the second time point is higher than the level at the first time point; wherein an indication by the at least one value, for each gene of the set, that the level at the second time point is higher than the level at the first time point indicates a progression of heart failure. In one embodiment step c) is effected by causing a suitably programmed computer to compare a level of RNA encoded by a gene at a first time point to a level of RNA encoded by the gene at a second time point to thereby determine the at least one value indicating whether the level at the second time point is higher than the level at the first time point.

In another aspect, there is provided a method of monitoring the progression of heart failure in a human subject, the method comprising, for each gene of a set of one or more of the genes listed in Table 7: a) determining a level of RNA encoded by the gene in blood of the subject at a first time point; b) determining a level of RNA encoded by the gene in blood of the subject at a second time point, wherein the second time point is later than the first time point; and c) comparing the levels of steps a) and b) to thereby determine at least one value indicating whether the level at the second time point is lower than the level at the first time point; wherein an indication by the at least one value, for each gene of the set, that the level at the second time point is lower than the level at the first time point indicates a progression of heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare a level of a RNA encoded by a gene at the first time point to a level of RNA encoded by the gene at the second time point to thereby determine the at least one value indicating whether the level at the second time point is lower than the level at the first time point.

According to yet another aspect, there is provided a computer-based method of monitoring the progression of heart failure in a human subject, the method comprising inputting, to a computer, test data representing a level of RNA encoded by one or more of the genes listed in Table 5 in blood of the subject at a first and at a second time point, wherein the second time point is later than the first time point; and causing the computer to compare the data of the first time point to the data of the second time point, and to determine whether the level at the second time is higher than the level at the first time point, wherein a determination that the level of RNA encoded by the gene in blood of the test subject at the second time point is higher than the level at the first time point indicates the progression of heart failure.

In an additional aspect, there is provided a computer-based method of monitoring the progression of heart failure in a human subject, the method comprising inputting, to a computer, test data representing a level of RNA encoded by one or more of the genes listed in Table 7 in blood of the subject at a first and second time point, wherein the second time point is later than the first time point; and causing the computer to compare the data of the first time point to the data of the second time point, and to determine whether the level at the second time point is lower than the level at the first time point, wherein a determination that the level at the second time point is lower than the level at the first time point indicates the progression of heart failure.

In another aspect, there is provided a method for classifying a human test subject as having heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Tables 5 and 6: a) determining a level of RNA encoded by the gene, thereby generating a test data; b) providing a control data representing a level of RNA encoded by the gene in blood of human control subjects, wherein the control subjects do not have heart failure; and c) comparing the test data to the control data to thereby determine at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of the control subjects, wherein an indication by the at least one value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of the control subjects classifies the test subject as having heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare the test data to the control data to thereby determine the at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of the control subject.

In another aspect, there is provided a method for classifying a human test subject as having heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Tables 7 and 8: a) determining a level of RNA encoded by the gene, thereby generating a test data; b) providing a control data representing a level of RNA encoded by the gene in blood of human control subjects, wherein the control subjects do not have heart failure; and c) comparing the test data to the control data to thereby determine at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of the control subjects, wherein an indication by the at least one value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of the control subjects classifies the test subject as having heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare the test data to the control data to thereby determine the at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of the control subject.

In another aspect, there is provided a method of classifying a human test subject as having decompensated heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Tables 5 and 6: a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating a test data; b) providing a control data representing a level of RNA encoded by the gene in blood of human control subjects not having heart failure; and c) comparing the test data to the control data to thereby determine at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having heart failure, wherein an indication by the at least one value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having heart failure classifies the test subject as having decompensated heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare the test data to the control data to thereby determine the at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having heart failure.

In yet another aspect, there is provided a method of classifying a human test subject as having decompensated heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Tables 7 and 8: a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating a test data; b) providing a control data representing a level of RNA encoded by the gene in blood of human control subjects not having heart failure; and c) comparing the test data to the control data to thereby determine at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having heart failure, wherein an indication by the at least one value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having heart failure classifies the test subject as having decompensated heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare the test data to the control data to thereby determine the at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having heart failure.

In a further aspect there is provided a computer-based method of classifying a human test subject as having decompensated heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Tables 5 and 6: inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the test subject; causing the computer to compare the test data to control data representing a level of RNA encoded by the gene in blood of human control subjects not having heart failure, and to determine whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having heart failure, wherein a determination that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having heart failure is used to classify the test subject as having decompensated heart failure.

In one aspect there is provided a method of classifying a human test subject as more likely to have NYHA class I-II heart failure than to not have heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Table 3: a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating a test data; b) providing a first positive control data representing levels of RNA encoded by the gene in blood of human control subjects having NYHA class I-II heart failure; and c) comparing the test data to the control data to thereby determine at least one value indicating whether the test data corresponds to the first positive control data; wherein an indication by the at least one value, for each gene of the set, that the test data corresponds to the first positive control data indicates that the test subject is more likely to have NYHA class I-II heart failure than not to have heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare a test data to a first positive control data to thereby determine at least one value indicating whether the test data corresponds to the first positive control data.

In one embodiment the method further provides: (d) providing a negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having heart failure; wherein a more likely correspondence between the test data and the positive control data than a correspondence between the test data and the negative control data indicates that the test subject is more likely to have NYHA class I-II heart failure than to not have heart failure.

In one embodiment, the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by the gene in blood of one or more subjects not having heart failure. In another embodiment, each gene of the set of one or more genes has a ROC AUC of at least 0.68, 0.70, 0.72, 0.74, 0.76, 0.78 and/or 0.80. In a further embodiment the ratio of the level of RNA encoded by at least one gene of the set of one or more genes in blood in the test subject compared to the control is less than about 0.90, 0.88, 0.86, 0.84, 0.82, 0.80 and/or 0.78. In a further embodiment the ratio of the level of RNA encoded by at least one gene of the set of one or more genes in blood in the test subject compared to the control is greater than about 1.20, 1.22, 1.24, 1.26, 1.28, 1.30, 1.32, 1.34, 1.36, 1.38 and/or 1.40. In some embodiments the ratio of the level of RNA encoded by each gene of the set of one or more genes in blood in the test subject compared to the control is the ratio at a sensitivity of 0.6. In still a further embodiment, the ratio of the level of RNA encoded by at least one gene of the set of one or more genes in blood in the test subject compared to the control is selected from a range which includes an extreme NYHA I-II/average control ratio, for example as set forth in Table 3 or Table 4.

In another aspect, there is provided a method of classifying a human test subject as more likely not to have heart failure than to have NYHA class I-II heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Table 3: a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating a test data; b) providing a first positive control data representing levels of RNA encoded by the gene in blood of human control subjects not having heart failure; and c) comparing the test data to the control data to thereby determine at least one value indicating whether the test data corresponds to the first positive control data; wherein an indication by the at least one value, for each gene of the set, that the test data corresponds to the first positive control data indicates that the test subject is more likely not to have heart failure than to have NYHA class I-II heart failure.

In one embodiment, step c) is effected by causing a suitably programmed computer to compare the data of steps a) and b) to thereby determine the at least one value indicating whether the test data corresponds to the first positive control data.

In one embodiment the method further comprises: (d) providing a first positive control data representing levels of RNA encoded by the gene in blood of human control subjects having NYHA class I-II heart failure; wherein a more likely correspondence between the test data and the negative control data than a correspondence between the test data and the first positive control data indicates that the test subject is more likely to not have heart failure than to have NYHA class I-II heart failure.

In one embodiment, the ratio of the level of RNA encoded by each gene of the set of one or more genes gene in blood in the test subject compared to the control is the ratio at a specificity of 0.6. In a further embodiment, the ratio of the level of RNA encoded by each gene of the set of one or more genes gene in blood in the test subject compared to the control is selected from a range which includes an extreme control/average control ratio, for example as set forth in Table 3 or Table 4.

In still a further aspect, there is provided a method of classifying a human test subject as more likely to have NYHA class III-IV heart failure than not to have heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Table 4: a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating a test data; b) providing a first positive control data representing levels of RNA encoded by the gene in blood of human control subjects having NYHA class III-IV heart failure; and c) comparing the levels of (a) and (b) to thereby determine at least one value indicating whether the test data corresponds to the first positive control data; wherein an indication by the at least one value, for each gene of the set, that the test data corresponds to the first positive control data classifies the test subject as more likely to have NYHA class III-IV heart failure than not to have heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare the levels of (a) and (b) to thereby determine at least one value indicating whether the test data corresponds to the first positive control data.

In one embodiment, the method further provides: (d) providing a negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having heart failure; wherein a more likely correspondence between the test data and the positive control data than a correspondence between the test data and the negative control data indicates that the test subject is more likely to have NYHA class III-IV heart failure than to not have heart failure.

In one embodiment each gene of the set of one or more genes has a ROC AUC of at least 0.60, 0.64, 0.68, 0.70, 0.72, 0.74, 0.76, 0.78 and/or 0.80. In another embodiment, the ratio of the level of RNA encoded by at least one gene of the set of one or more genes gene in blood in the test subject compared to the control is less than about 0.90, 0.80, 0.86, 0.84, 0.82, 0.80, 0.78, 0.76, 0.74, 0.72 and/or 0.7. In a further embodiment, the ratio of the level of RNA encoded by at least one gene of the set of one or more genes gene in blood in the test subject compared to the control is greater than about 1.20, 1.22, 1.24, 1.26, 1.28, 1.30, 1.32, 1.34, 1.36, 1.38, 1.40, 1.42, 1.44, 1.46, 1.48, 1.5 and/or 1.52. In some embodiments, the ratio of the level of RNA encoded by each gene of the set of one or more genes in blood in the test subject compared to the control is the ratio at a sensitivity of 0.6. In yet another embodiment, the ratio of the level of RNA encoded by each gene of the set of one or more genes in blood in the test subject compared to the control is selected from a range which includes an extreme NYHA III-IV/average control ratio, for example as set forth in Table 3 or Table 4.

In another aspect of the disclosure, there is provided a method of classifying a human test subject as more likely to not have heart failure than to have NYHA class III-IV heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Table 4: a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating a test data; b) providing a first positive control data representing levels of RNA encoded by the gene in blood of human control subjects having NYHA class III-IV heart failure; and c) comparing the data of steps a) and b) to thereby determine at least one value indicating whether the test data corresponds to the first positive control data; wherein an indication by the at least one value, for each gene of the set, that the test data corresponds to the first positive control data classifies the test subject as more likely not to have heart failure than to have NYHA class III-IV heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare a test data to a control data to thereby determine at least one value indicating whether the test data corresponds to a first positive control data.

In one embodiment, the method further provides: (d) providing a positive control data representing levels of RNA encoded by the gene in blood of human control subjects having NYHA class III-IV heart failure; wherein a more likely correspondence between the test data and the negative control data than a correspondence between the test data and the first positive control data indicates that the test subject is more likely to not have heart failure than to have NYHA class III-IV heart failure.

In one embodiment, the ratio of the level of RNA encoded by each gene of the set of one or more genes in blood in the test subject compared to the control is the ratio at a specificity of 0.6. In another embodiment, the ratio of the level of RNA encoded by each gene of the set of one or more genes in blood in the test subject compared to the control is selected from a range which includes an extreme control/average control ratio, for example as set forth in Table 3 or Table 4.

In various aspects the disclosure provides computer-based methods for classifying human test subjects in relation to heart failure.

Accordingly, in one aspect of the disclosure there is provided a computer-based method for classifying a human test subject as more likely to have NYHA class I-II heart failure than to not have heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Table 3: inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the test subject; and causing the computer to compare the test data to a first positive control data representing levels of RNA encoded by the gene in blood of human control subjects having heart failure, wherein correspondence between the test data and the first positive control data classifies the subject as more likely to have NYHA class I-II heart failure than to not have heart failure.

In another aspect of the disclosure there is provided a computer-based method for classifying a human test subject as more likely to not have heart failure than to have NYHA I-II heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Table 3: inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the test subject; and causing the computer to compare the test data to a first negative control data representing levels of RNA encoded by the gene in blood of human control subjects having heart failure, wherein correspondence between the test data and the first negative control data classifies the subject as more likely not to have heart failure than to have NYHA class I-II heart failure.

In yet another aspect of the disclosure there is provided a computer-based method for classifying a human test subject as more likely to have NYHA class III-IV heart failure than to not have heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Table 4: inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the test subject; and causing the computer to compare the test data to a first positive control data representing levels of RNA encoded by the gene in blood of human control subjects having heart failure, wherein correspondence between the test data and the first positive control data classifies the subject as more likely to have NYHA class III-IV heart failure than to not have heart failure.

In still another aspect of the disclosure, there is provided a computer-based method for classifying a human test subject as more likely to not have heart failure than to have NYHA class III-IV heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Table 4: inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the test subject; and causing the computer to compare the test data to a first negative control data representing levels of RNA encoded by the gene in blood of human control subjects having heart failure, wherein correspondence between the test data and the first negative control data classifies the subject as more likely to not have failure than to have NYHA class III-IV heart failure.

In yet a further aspect, there is provided a computer-based method of classifying a human test subject as having decompensated heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Tables 7 and 8: inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the test subject; and causing the computer to compare the test data to a control data representing a level of RNA encoded by the gene in blood of human control subjects not having heart failure, and to determine whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having heart failure, wherein a determination that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having heart failure is used to classify the test subject as having decompensated heart failure.

According to still another aspect of the disclosure there is provided a kit comprising packaging and containing, for each gene of a set of one or more of the genes listed in Table 1 a primer set capable of generating an amplification product of DNA complementary to RNA encoded, in a human subject, only by the gene.

According to further features of the disclosure described below, the kit further comprises a computer-readable medium having instructions stored thereon that are operable when executed by a computer for comparing a test data representing a level of RNA encoded by the gene in blood of a human test subject to a first positive control data representing levels of RNA encoded by the gene in blood of human control subjects having a first categorized severity of heart failure, to thereby determine at least one value indicating whether the test data corresponds to the control data wherein an indication by the at least one value that the test data corresponds to the first positive control data classifies the test subject as having the first categorized severity of heart failure.

In another embodiment, the computer readable medium further has instructions stored thereon that are operable when executed by a computer for comparing a second positive control data representing levels of RNA encoded by the gene in blood of human control subjects having a second categorized severity of heart failure, wherein correspondence between the test data and the second positive control data indicates that the test subject has the second categorized severity of heart failure.

In yet another aspect, there is provided a kit comprising packaging and containing, for each gene of a set of one or more of the genes listed in Table 1, a primer set capable of generating an amplification product of DNA complementary to RNA encoded, in a human subject, only by the gene.

According to further features of the disclosure described below, the kit further comprises a thermostable polymerase, a reverse transcriptase, deoxynucleotide triphosphates, nucleotide triphosphates and/or enzyme buffer.

According to further features of the disclosure described below, the kit further comprises at least one labeled probe capable of selectively hybridizing to either a sense or an antisense strand of the amplification product.

According to further features of the disclosure described below, the level of RNA encoded by the gene in blood of the test subject is determined by quantitative reverse transcriptase-polymerase chain reaction analysis.

According to further features of the disclosure described below, the level of RNA encoded by the gene in blood of the test subject is determined by probing a microarray.

According to further features of the disclosure described below, the level of RNA encoded by the gene in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined by the same method.

In further aspects, there is provided isolated compositions, test systems and primer sets for use in the methods disclosed herein.

Other features and advantages of the present disclosure will become apparent from the following detailed description. It should be understood, however, that the detailed description and the specific examples while indicating preferred embodiments of the disclosure are given by way of illustration only, since various changes and modifications within the spirit and scope of the disclosure will become apparent to those skilled in the art from this detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

An embodiment of the disclosure will now be described in relation to the drawings in which:

FIG. 1 shows an exemplary computer system.

DETAILED DESCRIPTION OF THE DISCLOSURE

As will become apparent, preferred features and characteristics of one aspect are applicable to any other aspect. It should be noted that, as used herein, the singular form “a”, “an” and “the” include plural references unless the context clearly dictates otherwise.

The term “encode” as used herein means that a polynucleotide, including a gene, is said to “encode” a RNA and/or polypeptide if, in its native state or when manipulated by methods well known to those skilled in the art, it can be transcribed and/or translated to produce the mRNA for and/or the polypeptide or a fragment thereof. The anti-sense strand is the complement of such a nucleic acid, and the encoding sequence can be deduced there from.

The term “label” as used herein refers to a composition capable of producing a detectable signal indicative of the presence of the target polynucleotide in an assay sample. Suitable labels include radioisotopes, nucleotide chromophores, enzymes, substrates, fluorescent molecules, chemiluminescent moieties, magnetic particles, bioluminescent moieties, and the like. As such, a label is any composition detectable by spectroscopic, photochemical, biochemical, immunochemical, electrical, optical or chemical means.

As used herein, a “sample” refers to a sample of tissue or fluid isolated from an individual, including but not limited to, for example, blood, plasma, serum, tumor biopsy, urine, stool, sputum, spinal fluid, pleural fluid, nipple aspirates, lymph fluid, the external sections of the skin, respiratory, intestinal, and genitourinary tracts, tears, saliva, milk, cells (including but not limited to blood cells), organs, and also samples of in vitro cell culture constituent.

The term “gene” as used herein is a polynucleotide which may include coding sequences, intervening sequences and regulatory elements controlling transcription and/or translation. Genes of the disclosure include normal alleles of the gene encoding polymorphisms, including silent alleles having no effect on the amino acid sequence of the gene's encoded polypeptide as well as alleles leading to amino acid sequence variants of the encoded polypeptide that do not substantially affect its function. These terms also may optionally include alleles having one or more mutations which affect the function of the encoded polypeptide's function.

The polynucleotide compositions, such as primers, of this disclosure include RNA, cDNA, DNA complementary to target cDNA of this disclosure or portion thereof, genomic DNA, unspliced RNA, spliced RNA, alternately spliced RNA, synthetic forms, and mixed polymers, both sense and antisense strands, and may be chemically or biochemically modified or may contain non-natural or derivatized nucleotide bases, as will be readily appreciated by those skilled in the art.

Where nucleic acid according to the disclosure includes RNA, reference to the sequence shown should be construed as reference to the RNA equivalent, with U substituted for T.

The term “amount” or “level” of RNA encoded by a gene described herein encompasses the absolute amount of the RNA, the relative amount or concentration of the RNA, as well as any value or parameter which correlates thereto.

The methods of nucleic acid isolation, amplification and analysis are routine for one skilled in the art and examples of protocols can be found, for example, in the Molecular Cloning: A Laboratory Manual (3-Volume Set) Ed. Joseph Sambrook, David W. Russel, and Joe Sambrook, Cold Spring Harbor Laboratory; 3rd edition (Jan. 15, 2001), ISBN: 0879695773. Particularly useful protocol source for methods used in PCR amplification is PCR (Basics: From Background to Bench) by M. J. McPherson, S. G. Moller, R. Beynon, C. Howe, Springer Verlag; 1st edition (Oct. 15, 2000), ISBN: 0387916008.

“Heart failure” as used herein means a condition that impairs the ability of the heart to fill with blood or pump a sufficient amount of blood through the body resulting from a structural or functional cardiac disorder. Heart failure may be interchangeably referred to as congestive heart failure (CHF) or congestive cardiac failure (CCF). Stages of heart failure may be defined using any one of various classification systems known in the art. For example, heart failure may be classified using the New York Heart Association (NYHA) classification system. According to the NYHA classification system, there are 4 main classes of heart failure; NYHA stage I (NYHA I) heart failure, NYHA stage II (NYHA II) heart failure. NYHA stage III (NYHA III) heart failure and NYHA stage IV (NYHA IV) heart failure. These stages classify heart failure according to the following: NYHA I: No symptoms and no limitation in ordinary physical activity; NYHA II: Mild symptoms (mild shortness of breath and/or angina pain) and slight limitation during ordinary activity; NYHA III: Marked limitation in activity due to symptoms, even during less-than-ordinary activity (e.g. walking short distances, about 20 to 100 meters). Comfortable only at rest; NYHA IV: Severe limitations. Symptoms are experienced even while at rest, mostly bedbound patients.

As used herein, “Compensated heart failure” corresponds to NYHA I/NYHA II heart failure.

As used herein, “Decompensated heart failure” means corresponds to NYHA III/NYHA IV heart failure.

A “control population” refers to a defined group of individuals or a group of individuals with or without heart failure or with a particular heart failure classification, and may optionally be further identified by, but not limited to geographic, ethnic, race, gender, one or more other conditions or diseases, and/or cultural indices. In most cases a control population may encompass at least 10, 50, 100, 1000, or more individuals.

“Positive control data” encompasses data representing levels of RNA encoded by a target gene disclosed herein in each of one or more subjects having heart failure or a particular heart failure classification, and encompasses a single data point representing an average level of RNA encoded by a target gene in a plurality of subjects having heart failure or the particular heart failure classification.

“Negative control data” encompasses data representing levels of RNA encoded by a target gene described herein in each of one or more subjects not having heart failure, and encompasses a single data point representing an average level of RNA encoded by a target gene of the disclosure in a plurality of subjects not having heart failure.

According to one embodiment, subjects not having heart failure are healthy subjects.

The probability that test data “corresponds” to positive control data or negative control data refers to the probability, when comparing to positive control data, that the test data is more likely to be characteristic of data obtained in subjects having heart failure or the particular heart failure classification than in subjects not having any heart failure or the particular heart failure classification, or, when comparing to negative control data, that the test data is more likely to be characteristic of data obtained in subjects not having any heart failure or the particular heart failure classification than in subjects having heart failure or the particular heart failure classification, respectively.

A gene expression profile for heart failure or a particular heart failure classification found in blood at the RNA level of one or more of the genes listed in Tables 1, 3, 4, 5, 6, 7 and 8, can be identified or confirmed using many techniques, including but preferably not limited to PCR methods, as for example discussed further in the working examples herein, Northern analyses and the microarray technique. This gene expression profile can be measured in a bodily sample, such as blood, using microarray technology. In an embodiment of this method, fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from blood. Labeled cDNA probes applied to the chip hybridize with specificity to each spot of DNA on the array. Quantitation of hybridization of each arrayed element allows for assessment of corresponding mRNA abundance. For example, with dual color fluorescence, separately labeled cDNA probes generated from two sources of RNA are hybridized pair wise to the array. The relative abundance of the transcripts from the two sources corresponding to each specified gene is thus determined simultaneously. Such methods have been shown to have the sensitivity required to detect rare transcripts, which are expressed at a few copies per cell, and to reproducibly detect at least approximately two-fold differences in the expression levels (Schena et al., Proc. Natl. Acad. Sci. USA 93(2):106-149 (1996)). Microarray analysis can be performed by commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GenChip technology, or Incyte's microarray technology.

The phrase “receiver operating characteristic” or ROC curve, as used herein refers to a plot of true positive versus false positive results, usually in a trial of a diagnostic test. A ROC curve is a graphical means of assessing the ability of a screening test to discriminate between healthy/non-diseased and diseased persons.

The term “specificity” as used herein means the percentage of subjects who do not have a disorder (e.g. heart failure), or stage/class thereof, who are identified by an assay for the disorder, or stage/class thereof, as negative for the disorder, or stage/class thereof, respectively.

The term “sensitivity” as used herein means the percentage of subjects who have a disorder, or stage/class thereof, who are identified by an assay for the disorder, or stage/class thereof, as positive for the disorder, or stage/class thereof, respectively.

The phrase “threshold fold-change” as used herein refers to a fold change expression level threshold relative to average of subjects not having heart failure that is suitable for classifying a test subject, for example classifying a test subject as more likely to have NYHA class I-II heart failure than to not have heart failure at a particular sensitivity (e.g. 0.6) or specificity (e.g. 0.6).

The phrase “extreme NYHA/average control” is a ratio of the extreme directional NYHA subject expression level of a gene to the average control expression level of the gene. The ratio is useful to limit a range of fold-change expression which classifies a test subject, for example as more likely to have heart failure or a stage/class thereof, than to not have heart failure. For a gene which is overexpressed in subjects having heart failure or stage/class thereof relative to subjects not having heart failure (having a fold-change relative to average expression in subjects not having heart failure which is greater than 1), “extreme NYHA/average control” is a ratio of the highest level of gene expression observed in a subject having heart failure, or the stage/class thereof, relative to average expression in subjects not having heart failure (e.g. healthy controls), for example, as exemplified in Table 3 or Table 4, based on data provided in Table 1. For a gene which is underexpressed in subjects having heart failure, or a stage/class thereof relative to subjects not having heart failure, or the class/stage thereof, (having a fold-change relative to average expression in subjects not having heart failure which is less than 1), “extreme NYHA/average control” is a ratio of the lowest level of gene expression observed in a subject having heart failure, or the stage/class thereof, relative to average expression in subjects not having heart failure (e.g. healthy subjects), for example, as exemplified in Table 3 or Table 4, based on data provided in Table 1.

The phrase “extreme control/average control” as used herein is a ratio of the extreme directional control subject expression level of a gene to the average control expression level for the gene. The ratio is useful as a limit to the range of fold-change expression which classifies a test subject, for example as more likely to not have heart failure, or a stage/class thereof, than to have heart failure or a stage/class thereof. For a gene which is overexpressed in subjects having heart failure, or a stage/class thereof, relative to subjects not having heart failure (having a fold-change relative to average expression in subjects not having heart failure which is greater than 1), “extreme control/average control” is a ratio of the lowest level of gene expression observed in a control subject not having heart failure sample (e.g. healthy control) relative to average expression in control subjects not having heart failure (e.g. healthy controls), for example, as exemplified in Table 3 or Table 4, based on data provided in Table 1. For a gene which is underexpressed in subjects having heart failure, or a stage/class thereof, relative to subjects not having heart failure (having a fold-change relative to average expression in subjects not having heart failure which is less than 1), “extreme control/average control” is a ratio of the highest level of gene expression observed in a control subject not having heart failure (e.g. healthy control) relative to average expression in control subjects not having heart failure (e.g. healthy control subjects), for example, as exemplified in Table 3 or Table 4, based on data provided in Table 1.

Methods

According to one aspect, there is provided a method of determining whether a human test subject has heart failure as opposed to not having heart failure, the method comprising for each gene of a set of one or more of the genes listed in Tables 1, 3, 4, 5, 6, 7, and 8: a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating a test data; b) providing a positive control data representing levels of RNA encoded by the gene in blood of human control subjects having heart failure and a negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having heart failure; and c) comparing the data of steps a) and b) to thereby determine at least one value indicating whether the test data corresponds to the positive control data or the negative control data; wherein an indication by the at least one value, for each gene of the set, that the test data corresponds to the positive control data and not to the negative control data classifies the test subject as having heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare the data of steps a) and b) to thereby determine the at least one value indicating whether the test data corresponds to the positive control data or the negative control data.

According to another aspect, there is provided a method of determining a severity of heart failure in a human test subject, the method comprising for each gene of a set of one or more of the genes listed in Tables 5, 6, 7 and 8: a) determining a level of RNA encoded by the gene in blood of the test subject', thereby generating a test data; (b) providing a first positive control data representing levels of RNA encoded by the gene in blood of human control subjects having a first categorized severity of heart failure; and c) comparing the levels of steps a) and b) to thereby determine at least one value indicating whether the test data corresponds to the positive control data; wherein an indication by the at least one value, for each gene of the set, that the test data corresponds to the first positive control data classifies the test subject as having the first categorized severity of heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare the levels of steps a) and b) to thereby determine the at least one value indicating whether the test data corresponds to the positive control data.

In one embodiment, the first categorized severity is compensated heart failure or decompensated heart failure.

In another embodiment, the method further comprises providing a second positive control data representing levels of RNA encoded by the gene in blood of human control subjects having a second categorized severity of heart failure, wherein correspondence between the test data and the second positive control data indicates that the test subject has the second categorized severity of heart failure. In one embodiment, the first categorized severity is compensated heart failure and the second categorized severity is decompensated heart failure. In such an embodiment, the method allows determination of the likelihood that a particular heart failure patient falls within a compensated heart failure class or a decompensated heart failure class, which is relevant to types of treatment available to the subject.

In an embodiment, the method further comprises determining levels of RNA encoded by the gene in blood of a population of human subjects having the first categorized severity of heart failure, thereby providing the positive control data representing the levels of RNA encoded by the gene in blood of human control subjects having the first categorized severity of heart failure. In yet another embodiment, the method further comprises determining levels of RNA encoded by the gene in blood of a population of human subjects having the second categorized severity of heart failure, thereby providing the positive control data representing the levels of RNA encoded by the gene in blood of human control subjects having the second categorized severity of heart failure.

In a further embodiment, the method further comprises providing a third control data representing levels of RNA encoded by the gene in blood of human control subjects which not having heart failure, and wherein step c) is effected by comparing the test data to the first or second positive control data and the third control data, wherein correspondence with the first or second positive control data and not the third control data indicates that the test subject has the first or second categorized severity of heart failure.

In a further aspect, there is provided a method of monitoring the progression of heart failure in a human subject, the method comprising for each gene of a set of one or more of the genes listed in Table 5: a) determining a level of RNA encoded by the gene in blood of the subject at a first time point; b) determining a level of RNA encoded by the gene in blood of the subject at a second time point, wherein the second time point is later than the first time point; and c) comparing the levels of steps a) and b) to thereby determine at least one value indicating whether the level at the second time point is higher than the level at the first time point; wherein an indication by the at least one value, for each gene of the set, that the level at the second time point is higher than the level at the first time point indicates a progression of heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare a level of RNA encoded by a gene at a first time point to a level of RNA encoded by the gene at the second time point to thereby determine at least one value indicating whether the level at the second time point is higher than the level at the first time point.

In another aspect, there is provided a method of monitoring the progression of heart failure in a human subject, the method comprising, for each gene of a set of one or more of the genes listed in Table 7: a) determining a level of RNA encoded by the gene in blood of the subject at a first time point; b) determining a level of RNA encoded by the gene in blood of the subject at a second time point; and c) comparing the levels of steps a) and b) to thereby determine at least one value indicating whether the level at the second time point is lower than the level at the first time point; wherein an indication by the at least one value, for each gene of the set, that the level at the second time point is lower than the level at the first time point indicates a progression of heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare a level of RNA encoded by a gene at the first time point to a level of RNA encoded by the gene at the second time point to thereby determine the at least one value indicating whether the level at the second time point is lower than the level at the first time point.

In another aspect, there is provided a method for classifying a human test subject as having heart failure comprising, for each gene of a set of one or more of the genes listed in Tables 5 and 6: a) determining a level of RNA encoded by the gene, thereby generating a test data; b) providing a control data representing a level of RNA encoded by the gene in blood of human control subjects, wherein the control subjects do not have heart failure; and c) comparing the test data to the control data to thereby determine at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the levels of RNA encoded by the gene in blood of the control subjects, wherein an indication by the at least one value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of the control subjects classifies the test subject as having heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare the test data to the control data to thereby determine the at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the levels of RNA encoded by the gene in blood of the control subjects.

In another aspect, there is provided a method for classifying a human test subject as having heart failure comprising, for each gene of a set of one or more of the genes listed in Tables 7 and 8: a) determining a level of RNA encoded by the gene, thereby generating a test data; b) providing control data representing levels of RNA encoded by the gene in blood of human control subjects wherein the control subjects do not have heart failure; and c) comparing the test data to the control data to thereby determine at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of the control subjects, wherein an indication by the at least one value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of the control subjects classifies the test subject as having heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare the test data to the control data to thereby determine the at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of the control subjects.

In a further aspect, there is provided a method of classifying a human test subject as having decompensated heart failure, the method comprising a) determining a level of RNA encoded by each gene of a set of one or more of the genes listed in Table 5 in blood of the test subject, thereby generating a test data; b) providing a control data representing a level of RNA encoded by the gene in blood of human control subjects not having heart failure; and c) comparing the test data to the control data to thereby determine at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having heart failure, wherein an indication by the at least one value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having heart failure classifies the test subject as having decompensated heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare the test data to the control data to thereby determine the at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having heart failure.

In yet another aspect, there is provided a method of classifying a human test subject as having decompensated heart failure, the method comprising for each gene of a set of one or more of the genes listed in Table 7: a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating a test data; b) providing a control data representing a level of RNA encoded by the gene in blood of human control subjects not having heart failure; and c) comparing the test data to the control data to thereby determine at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having heart failure, wherein an indication by the at least one value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having heart failure classifies the test subject as having decompensated heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare a test data to a control data to thereby determine the at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having heart failure.

Determining whether the level of RNA of a gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of control subjects not having heart failure or in the same subject at a different time point may be effected by determining whether there is a fold-change in the level between the test subject and the control subjects or different time point which is higher than a minimum fold-change and/or which is within a range of fold-changes.

Determining whether the level of RNA of a gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of control subjects not having heart failure or in the same subject at a different time point may be effected by determining whether there is a fold-change in the level between the test subject and the control subjects or different time point which is lower than a maximum fold-change and/or which is within a range of fold-changes.

For a gene which is overexpressed in subjects having heart failure or stage/class thereof relative to subjects not having heart failure (having a fold-change relative to average expression in subjects not having heart failure which is greater than 1), a test subject having an expression level of the gene relative to average of subjects not having heart failure which equals or exceeds a threshold fold-change for sensitivity (e.g. average fold-change expression at sensitivity=0.6, as indicated in Table 3 and Table 4) is classified as being more likely to have heart failure or the stage/class thereof than to not have heart failure.

For a gene which is overexpressed in subjects having heart failure or stage/class thereof relative to subjects not having heart failure, a test subject having an expression level of the gene which is below the threshold fold-change for specificity (e.g. average fold-change expression at specificity=0.6, as indicated in Table 3 and Table 4) is classified as more likely to not have heart failure than to have heart failure or the stage/class thereof.

For a gene which is underexpressed in subjects having heart failure or stage/class thereof relative to subjects not having heart failure (having a fold-change relative to average expression in subjects not having heart failure which is less than 1), a test subject having an expression level of the gene relative to average of subjects not having heart failure which is less than or equal to the threshold fold-change for sensitivity (e.g. average fold-change expression at sensitivity=0.6, as indicated in Table 3 and Table 4) is classified as being more likely to have the heart failure or the stage/class thereof than to not have heart failure.

For a gene which is underexpressed in subjects having heart failure or stage/class thereof relative to subjects not having heart failure, a test subject having an expression level of the gene which is greater than the threshold fold-change for specificity (e.g. average fold-change expression at specificity=0.6, as indicated in Table 3 and Table 4) is classified as more likely to not have heart failure than to have heart failure or the stage/class thereof.

Optionally, the range of fold-changes classifying a test subject as more likely to have heart failure or the stage thereof than to not have heart failure may include, and be limited by, the extreme directional fold-change observed (Extreme NYHA/average Control), indicated in Table 3 and Table 4, as well as by the threshold fold-change at a given sensitivity. Further, optionally, the range of fold-changes classifying a test subject as more likely to not have heart failure than to have heart failure or the stage thereof may be limited by the extreme directional fold-change observed (Extreme Control/average Control), as indicated in Table 3 and Table 4, as well as by the threshold fold-change at a given specificity.

Examples of suitable fold-changes and ranges of fold-changes for classifying a test subject are provided in Tables 3, 4, 5, 6, 7 and 8, and include the following ones. The methods recited in the above and below paragraphs can be done with “about” the cited amounts.

A person skilled in the art will recognize that accuracy of classification power of the genes in terms of ROC AUC increases with increasing ROC AUC values.

Accordingly, in one embodiment, each gene of the set of one or more genes has a ROC AUC of at least 0.68, 0.70, 0.72, 0.74, 0.76, 0.78 and/or 0.80.

In certain embodiments, the genes in the gene set comprise genes having a particular fold change expression compared to control.

In one embodiment, wherein the level of gene expression in a class of heart failure is increased, the fold change to classify a test subject as NYHA I-U, a suitable minimum fold-change is about 1.20, 1.22, 1.24, 1.26, 1.28, 1.30, 1.32, 1.34, 1.36, 1.38, 1.40, 1.42, 1.44, 1.46, 1.48, 1.5 and/or 1.52 fold and/or greater than 1.52 fold, and a suitable range of fold-changes is about 1.20 to 1.7 fold, 1.25-1.65 fold, 1.30-1.60 fold, 1.35 to 1.55 fold, 1.40 to 1.50 fold, relative to an average level of RNA encoded by the gene in blood of subjects not having heart failure. To classify a test subject as NYHA-III-IV, a suitable minimum fold-change is greater than or equal about 1.20, 1.22, 1.24, 1.26, 1.28, 1.30, 1.32, 1.34, 1.36, 1.38, 1.40, 1.42, 1.44, 1.46, 1.48, 1.50, 1.52, 1.60, 1.70, 1.80, 1.90 and/or 2.00 fold and/or greater than 2.00 fold, and a suitable range of fold-changes is about 1.20 to 2.10 fold, 1.25 to 2.10 fold, 1.30 to 2.10 fold, 1.35 to 2.10 fold, 1.40 to 2.10 fold, relative to an average level of RNA encoded by the gene in blood of subjects not having heart failure.

In one embodiment wherein the level of gene expression in a class of heart failure is decreased, the fold change to classify a test subject as NYHA I-II, and/or NYHA III/IV a suitable minimum fold-change is about is less than about 0.90, 0.80, 0.86, 0.84, 0.82, 0.80 and/or 0.7 and a suitable range of fold-changes is about 0.90 to 0.60 fold, 0.88 to 0.60 fold, 0.84 to 0.60 fold, 0.80 to 0.6 fold, 0.76 to 0.60 fold, 0.72 to 0.60 fold, or 0.68 to 0.60 fold

In addition a cut-off value corresponding to a desired specificity and or specificity can be selected. In one embodiment, the sensitivity is 0.6. In another embodiment, the specificity is 0.6.

As used herein, the term “about” refers to a variability of plus or minus 10 percent.

Thus, a test subject is classified or determined as having or being more likely to have heart failure or a particular heart failure classification than to not have it if, for each marker gene of the particular set of marker genes used to practice the method of classifying or determining, the fold-change in level of RNA encoded by that gene in blood of the test subject relative to blood of the control subjects not having heart failure or the particular heart failure classification, classifies or determines that the test subject has or is more likely to have heart failure or the particular heart failure classification than to not have it.

Conversely, a test subject is classified or determined as having or being more likely to not have heart failure or the particular heart failure classification if for each marker gene of the particular set of marker genes used to practice the method of classifying or determining, the fold-change in level of RNA encoded by that gene in blood of the test subject relative to blood of the control subjects does not classify or determine the test subject as having or being more likely to have heart failure or the particular heart failure classification than to not have it.

In one aspect, the set of one or more heart failure marker genes may consist of any one of the possible combinations of one or more of the genes set out in Tables 1, 3, 4, 5, 6, 7, and 8.

In an aspect of the present disclosure, the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by the gene in blood of a test subject not having heart failure.

It will be appreciated that data representing levels of RNA encoded by a set of genes of the disclosure may be combined with data representing levels of gene products of other genes which are differently expressed in blood in subjects having heart failure relative to subjects not having any heart failure so as to determine a probability that a test subject has heart failure versus not having heart failure, or for the purposes of classifying the stage of heart failure.

In another aspect, the method further comprises determining levels of RNA encoded by the gene in blood of a population of control human subjects having heart failure, and/or in blood of a population of human control subjects not having heart failure, to thereby provide the positive control data and/or the negative control data, respectively. Alternately, it is envisaged that the level of RNA encoded by a gene disclosed herein in control subjects of the disclosure could be provided by prior art data corresponding to a control data. In one embodiment, there is provided a first positive control data derived from subjects having a first categorized severity of heart disease, optionally, compensated or decompensated heart failure. In another embodiment, there is a first and second positive control data and the first positive control data is derived from subjects having compensated heart failure and the second positive control data is derived from subjects having decompensated heart failure.

The method may be practiced using any one of various types of control subjects.

In an aspect, the control subjects not having heart failure are subjects having been diagnosed as not having any heart failure as a result of routine examination. The methods disclosed herein may be practiced using subjects not having heart failure as the control subjects not having heart failure.

The methods described herein may furthermore be practiced using any one of various numbers of control subjects. One of ordinary skill in the art will possess the necessary expertise to select a sufficient number of control subjects so as to obtain control data having a desired statistical significance for practicing the method of the disclosure with a desired level of reliability.

For example, the method can be practiced using 1, 2, 3, 4, 5, 5 or more, 10 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, 100 or more, 10 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, 100 or more, 110 or more, 120 or more, 130 or more, 140 or more, 150 or more, 160 or more, 170 or more, 180 or more, 190 or more, or 200 or more of control subjects having heart failure and/ora particular classification of heart failure and/or of control subjects not having heart failure.

In one aspect of the disclosure, the level of RNA encoded by a gene in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined by the same method. As is described in the Examples section, below, the method can be practiced where the level of RNA encoded by a gene in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined by the same method. Alternately, it is envisaged that the level of a gene in blood of a test subject and in blood of control subjects could be determined using different methods. It will be appreciated that use of the same method to determine the levels of RNA encoded by a gene disclosed herein in a test subject and in control subjects can be used to avoid method-to-method calibration to minimize any variability which might arise from use of different methods.

In one aspect, determining of the level of RNA encoded by a gene disclosed herein in blood of a subject is effected by determining the level of RNA encoded by the gene in a blood sample isolated from the subject. Alternately, it is envisaged that determination of the level of RNA encoded by the gene in blood of a subject could be effected by determining the level of RNA encoded by the gene in an in-vivo sample using a suitable method for such a purpose.

In one aspect, the level of RNA encoded by a gene in blood of a subject is determined in a sample of RNA isolated from blood of the subject. Alternately, it is envisaged that the level of RNA of a gene in blood of a subject could be determined in a sample which includes RNA of blood of the subject but from which RNA has not been isolated therefrom, using a suitable method for such a purpose.

Any one of various methods routinely employed in the art for isolating RNA from blood may be used to isolate RNA from blood of a subject, so as to enable practicing of the methods described herein.

In one aspect, the level of RNA encoded by a gene in blood of a subject is determined in RNA of a sample of whole blood. Any one of various methods routinely employed in the art for isolating RNA from whole blood may be employed for practicing the method.

Alternately, it is envisaged that the level of RNA encoded by a gene in blood of a subject could be determined in RNA of a sample of fraction of blood which expresses the gene sufficiently specifically so as to enable the method. Examples of such blood fractions include preparations of isolated types of leukocytes, preparations of isolated peripheral blood mononuclear cells, preparations of isolated granulocytes, preparations of isolated whole leukocytes, preparations of isolated specific types of leukocytes, plasma-depleted blood, preparations of isolated lymphocytes, and the plasma fraction of blood.

In one aspect of the method, isolation of RNA from whole blood of a subject of the disclosure is effected using EDTA tubes, as described in the Examples section.

In another aspect of the method, isolation of RNA from whole blood of a subject of the disclosure may be effected by using a PAXgene Blood RNA Tube (obtainable from PreAnalytiX) in accordance with the instructions of the PAXgene Blood RNA Kit protocol.

Determination of a level of RNA encoded by a gene in a sample disclosed herein may be effected in any one of various ways routinely practiced in the art.

For example, the level of RNA encoded by a gene in a sample may be determined by any one of various methods based on quantitative polynucleotide amplification which are routinely employed in the art for determining a level of RNA encoded by a gene in a sample.

Alternatively, the level of RNA encoded by a gene may be determined by any one of various methods based on quantitative polynucleotide hybridization to an immobilized probe which are routinely employed in the art for determining a level of RNA encoded by a gene in a sample.

In one aspect of the methods described herein, quantitative polynucleotide amplification used to determine the level of RNA encoded by a gene is quantitative reverse transcriptase-polymerase chain reaction (PCR) analysis. Any one of various types of quantitative reverse transcriptase-PCR analyses routinely employed in the art to determine the level of RNA encoded by a gene in a sample may be used to practice the methods. For example, any one of various sets of primers may be used to perform quantitative reverse transcriptase-PCR analysis so as to practice the methods.

In one aspect, the quantitative reverse transcriptase-PCR analysis used to determine the level of RNA encoded by a gene is quantitative real-time PCR analysis of DNA complementary to RNA encoded by the gene using a labeled probe capable of specifically binding amplification product of DNA complementary to RNA encoded by the gene. For example, quantitative real-time PCR analysis may be performed using a labeled probe which comprises a polynucleotide capable of selectively hybridizing with a sense or antisense strand of amplification product of DNA complementary to RNA encoded by the gene. Labeled probes comprising a polynucleotide having any one of various nucleic acid sequences capable of specifically hybridizing with amplification product of DNA complementary to RNA encoded by the gene may be used to practice the methods described herein.

Quantitative real-time PCR analysis of a level of RNA encoded by a gene may be performed in any one of various ways routinely employed in the art.

In one aspect, quantitative real-time PCR analysis is performed by analyzing complementary DNA prepared from RNA of blood a subject of the disclosure, using the QuantiTect™ Probe RT-PCR system (Qiagen, Valencia, Calif.; Product Number 204345), a TaqMan dual labelled probe, and a Real-Time PCR System 7500 instrument (Applied Biosystems).

As specified above, the level of RNA encoded by a gene may be determined by a method based on quantitative polynucleotide hybridization to an immobilized probe.

In one aspect, determination of the level of RNA encoded by a gene by a method based on quantitative polynucleotide hybridization is effected using a microarray, such as an Affymetrix U133Plus 2.0 GeneChip oligonucleotide array (Affymetrix; Santa Clara, Calif.).

As specified above, the level of RNA encoded by a gene in a sample of the disclosure may be determined by quantitative reverse transcriptase-PCR analysis using any one of various sets of primers and labeled probes to amplify and quantitate DNA complementary to RNA encoded by a marker gene produced during such analysis. Examples of suitable primers for use in quantitative reverse transcriptase-PCR analysis of the level of RNA encoded by a target gene are within the knowledge of a person skilled in the art.

In one aspect, the primers may be selected so as to include a primer having a nucleotide sequence which is complementary to a region of a target cDNA template, where the region spans a splice junction joining a pair of exons. It will be appreciated that such a primer can be used to facilitate amplification of DNA complementary to messenger RNA, i.e. mature spliced RNA.

It will be appreciated that the probability that the test subject does not have any heart failure as opposed to having heart failure can be readily determined from the probability that the test subject has heart failure as opposed to not having heart failure. For example, when expressing the probability that the test subject has heart failure as a percentage probability, the probability that the test subject does not have any heart failure as opposed to having heart failure corresponds to 100 percent minus the probability that the test subject does not have any heart failure as opposed to having heart failure.

Determining the probability that the test data corresponds to positive control data and not to the negative control data may be effected in any one of various ways known to the ordinarily skilled artisan for determining the probability that a gene expression profile of a test subject corresponds to a gene expression profile of subjects having a pathology and not to a gene expression profile of subjects not having the pathology, where the gene expression profiles of the subjects having the pathology and the subjects not having the pathology are significantly different.

In one aspect of the method, determining the probability that the test data corresponds to the positive control data and not to the negative control data is effected by applying to the test data a mathematical model derived from the positive control data and from the negative control data.

In another aspect, determining whether the test data corresponds to positive control data may be effected in any one of various ways known to the ordinarily skilled artisan for determining whether a gene expression profile of a test subject corresponds to a gene expression profile of subjects having a pathology, where the gene expression profiles of the subjects having the pathology and the subjects not having the pathology are significantly different.

In one aspect, determining whether the test data corresponds to the positive control data is effected by applying to the test data a mathematical model derived from the positive control data.

Various suitable mathematical models which are well known in the art of medical diagnosis using disease markers may be employed to compare test data to a control data so as to classify, according to the present teachings, a test subject as more likely to have or having heart failure or a particular heart failure classification than to not have heart failure or the particular classification, to determine a probability that a test subject is likely to have heart failure or a particular heart failure classification as opposed to not having heart failure or the particular classification, or to diagnose a test subject as having colorectal cancer according to the teachings described herein. Generally these mathematical models can be unsupervised methods performing a clustering whilst supervised methods are more suited to classification of datasets. (refer, for example, to: Dreiseitl G. Ohno-Machado L. Logistic regression and artificial neural network classification models: a methodology review. J Biomed Inform. 2002 October-December; 35(5-6):352-9; Pepe M S. The Statistical Evaluation of Medical Tests for Classification and Prediction. Oxford, England: Oxford University Press; 2003; Dupont W D. Statistical Modeling for Biomedical Researchers. Cambridge, England: Cambridge University Press; 2002; Pampel F C. Logistic regression: A Primer. Publication #07-132, Sage Publications: Thousand Oaks, Calif. 2000; King E N, Ryan T P. A preliminary investigation of maximum likelihood logistic regression versus exact logistic regression. Am Statistician 2002; 56:163-170; Metz C E. Basic principles of ROC analysis. Semin Nucl Med 1978; 8:283-98; Swets J A. Measuring the accuracy of diagnostic systems. Science 1988; 240:1285-93; Zweig M H, Campbell G. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem 1993; 39:561-77; Witten I H, Frank Eibe. Data Mining: Practical Machine Learning Tools and Techniques (second edition). Morgan Kaufman 2005; Deutsch J M. Evolutionary algorithms for finding optimal gene sets in microarray prediction. Bioinformatics 200319:45-52; Niels Landwehr, Mark Hall and Eibe Frank (2003) Logistic Model Trees. pp 241-252 in Machine Learning: ECML 2003: 14th European Conference on Machine Learning, Cavtat-Dubrovnik, Croatia, Sep. 22-26, 2003, Proceedings Publisher: Springer-Verlag GmbH, ISSN: 0302-9743). Examples of such mathematical models, related to learning machine, include: Random Forests methods, logistic regression methods, neural network methods, k-means methods, principal component analysis methods, nearest neighbour classifier analysis methods, linear discriminant analysis, methods, quadratic discriminant analysis methods, support vector machine methods, decision tree methods, genetic algorithm methods, classifier optimization using bagging methods, classifier optimization using boosting methods, classifier optimization using the Random Subspace methods, projection pursuit methods, genetic programming and weighted voting methods.

Computer-Based Methods

It will be appreciated that a computer may be used for determining the probability that the test subject has heart failure or a particular classification using a mathematical model, according to the methods described herein.

Thus, according to another aspect of the disclosure there is provided a computer-based method of determining a severity of heart failure in a human test subject. Accordingly, there is provided a computer-based method of determining a severity of heart failure in a human test subject, the method comprising, for each gene of a set of one or more of the genes listed in Tables 1, 3, 4, 5, 6, 7 and 8: inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the test subject; and causing the computer to compare the test data to a first positive control data representing levels of RNA encoded by the gene in blood of human control subjects having a first categorized severity of heart failure, wherein correspondence between the test data and the first positive control data indicates that the test subject has the first categorized severity of heart failure.

In another aspect, there is provided computer-based method of monitoring the progression of heart failure in a human subject. Accordingly, there is provided a computer-based method of monitoring the progression of heart failure in a human subject, the method comprising, for each gene of a set of one or more of the genes listed in Table 5: inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the subject at a first and second time point, wherein the second time point is later than the first time point; and causing the computer to compare the data of the first time point to the data of the second time point to thereby determine at least one value indicating whether the level at the second time point is higher than the level at the first time point, wherein a determination that the level of RNA encoded by the gene in blood of the test subject is increased at the second time point indicates the progression of heart failure.

In an additional aspect, there is provided a computer-based method of monitoring the progression of heart failure in a human subject, the method comprising, for each gene of a set of one or more of the genes listed in Table 7: inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the subject at a first time point and a level of RNA encoded by the gene at a second time point; and causing the computer to compare the level at the first time point to the level at the second time point to thereby determine whether the level of RNA encoded by the gene in blood of the subject is decreased at the second time point compared to the level of RNA encoded by the gene in blood of the subject at the first time point, wherein a determination that the level of RNA encoded by the gene in blood of the test subject is decreased at the second time point indicates the progression of heart failure.

A further aspect of the disclosure provides a computer-based method of classifying a human test subject as having heart failure the method comprising, for each gene of a set of one or more of the genes listed in Tables 5 and 6: inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the test subject; causing the computer to compare the test data to a control data representing a level of RNA encoded by the gene in blood of human control subjects, wherein the control subjects do not have heart failure, to determine whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects; wherein a determination that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects is used to classify the test subject as having heart failure.

Yet a further aspect provides a computer-based method of Classifying a human test subject as having heart failure the method comprising for each gene of a set of one or more of the genes listed in Tables 7 and 8: inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the test subject; causing the computer to compare the test data to a control data representing a level of RNA encoded by the gene in blood of human control subjects, wherein the control subjects do not have heart failure, to determine whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects; and wherein a determination that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects is used to classify the test subject as having heart failure

Another aspect provides a method for classifying a human test subject as having compensated heart failure comprising, for each gene of a set of one or more of the genes listed in Tables 5 and 6: a) determining a level of RNA encoded by the gene, thereby generating a test data; b) providing control data representing levels of RNA encoded by the gene in blood of human control subjects, wherein the control subjects do not have heart failure; and c) comparing the test data to the control data, wherein a determination in step (c) that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of the control subjects indicates the test subject has heart failure.

Another aspect provides a method for classifying a human test subject as having compensated heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Tables 7 and 8: a) determining a level of RNA encoded by the gene, thereby generating a test data; b) providing a control data representing a level of RNA encoded by the gene in blood of human control subjects, wherein the control subjects do not have heart failure; and c) comparing the test data to the control data to thereby determine at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of the control subjects, wherein an indication by the at least one value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of the control subjects classifies the test subject as having heart failure. In one embodiment, step c) is effected by causing a suitably programmed computer to compare the test data to the control data to thereby determine the at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of the control subjects.

According to another aspect of the disclosure there is provided a computer-based method of classifying a human test subject as having decompensated heart failure. Accordingly, there is provided a computer-based method of classifying a human test subject as having decompensated heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Tables 5 and 6: inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the test subject; and causing the computer to compare the test data to a control data representing a level of RNA encoded by the gene in blood of human control subjects not having heart failure, and to determine whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having heart failure, wherein a determination that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having heart failure is used to classify the test subject as having decompensated heart failure.

In yet a further aspect, there is provided a computer-based method of classifying a human test subject as having decompensated heart failure, the method comprising, for each gene of a set of one or more of the genes listed in Tables 7 and 8, inputting, to a computer, test data representing a level of RNA encoded by the gene in blood of the test subject; and causing the computer to compare the test data to a control data representing a level of RNA encoded by the gene in blood of human control subjects not having heart failure, and to determine whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having heart failure, wherein a determination that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having heart failure is used to classify the test subject as having decompensated heart failure.

Application of computers for determining a probability that a test subject has a disease, or whether a test subject has a disease as opposed to not having the disease, so as to enable the method, is routinely practiced in the art using computer systems, and optionally computer-readable media, routinely used in the art.

Thus, according to a further aspect of the disclosure there is provided a computer system for providing the probability or determining that the test subject has heart failure or a particular classification as opposed to not having heart failure or the particular classification. The computer system comprises a processor; and a memory configured with instructions that cause the processor to provide a user with the probability or answer, where the instructions comprise applying a mathematical model to test data, to thereby determine the probability or whether the test subject has heart failure or the particular classification as opposed to not having heart failure or the particular classification.

The instructions may be provided to the computer in any one of various ways routinely employed in the art. In one aspect, the instructions are provided to the computer using a computer-readable medium.

Thus, according to yet another aspect of the disclosure there is provided a computer-readable medium having instructions stored thereon that are operable when executed by a computer for applying a mathematical model to test data, thereby determine the probability or whether a test subject has heart failure or the particular classification as opposed to not having heart failure or the particular classification.

As described above, following the step of obtaining the test data, the method of classifying of the disclosure comprises the step of comparing test data representing a level of RNA encoded by a marker gene to positive control data and/or negative control data, and determining the fold-change between the levels.

It will be appreciated that a computer may be used for comparing test data representing a level of RNA encoded by a marker gene to positive control data and/or negative control data, and determining the fold-change between the levels, according to methods of the disclosure.

An exemplary computer system for practicing certain of the methods described herein is described in FIG. 1.

FIG. 1 shows a schematic of a general-purpose computer system 100 suitable for practicing the methods described herein. The computer system 100, shown as a self-contained unit but not necessarily so limited, comprises at least one data processing unit (CPU) 102, a memory 104, which will typically include both high speed random access memory as well as non-volatile memory (such as one or more magnetic disk drives) but may be simply flash memory, a user interface 108, optionally a disk 110 controlled by a disk controller 112, and at least one optional network or other communication interface card 114 for communicating with other computers as well as other devices. At least the CPU 102, memory 104, user interface 108, disk controller where present, and network interface card, communicate with one another by at least one communication bus 106.

Memory 104 stores procedures and data, typically including: an operating system 140 for providing basic system services; application programs 152 such as user level programs for viewing and manipulating data, evaluating formulae for the purpose of diagnosing a test subject; authoring tools for assisting with the writing of computer programs; a file system 142, a user interface controller 144 for handling communications with a user by user interface 108, and optionally one or more databases 146 for storing data of the disclosure and other information, optionally a graphics controller 148 for controlling display of data, and optionally a floating point coprocessor 150 dedicated to carrying out mathematical operations. The methods of the disclosure may also draw upon functions contained in one or more dynamically linked libraries, not shown in FIG. 1, but stored either in Memory 104, or on disk 110, or accessible by network interface connection 114.

User interface 108 may comprise a display 128, a mouse 126, and a keyboard 130. Although shown as separate components in FIG. 1, one or more of these user interface components can be integrated with one another in embodiments such as handheld computers. Display 128 may be a cathode ray tube (CRT), or flat-screen display such as an LCD based on active matrix or TFT embodiments, or may be an electroluminescent display, based on light emitting organic molecules such as conjugated small molecules or polymers. Other embodiments of a user interface not shown in FIG. 1 include, e.g., several buttons on a keypad, a card-reader, a touch-screen with or without a dedicated touching device, a trackpad, a trackball, or a microphone used in conjunction with voice-recognition software, or any combination thereof, or a security-device such as a fingerprint sensor or a retinal scanner that prohibits an unauthorized user from accessing data and programs stored in system 100.

System 100 may also be connected to an output device such as a printer (not shown), either directly through a dedicated printer cable connected to a serial or USB port, or wirelessly, or by a network connection.

The database 146 may instead, optionally, be stored on disk 110 in circumstances where the amount of data in the database is too great to be efficiently stored in memory 104. The database may also instead, or in part, be stored on one or more remote computers that communicate with computer system 100 through network interface connection 114.

The network interface 134 may be a connection to the internet or to a local area network by a cable and modem, or ethernet, firewire, or USB connectivity, or a digital subscriber line. Preferably the computer network connection is wireless, e.g., utilizing CDMA. GSM, or GPRS, or bluetooth, or standards such as 802.11a, 802.11b, or 802.11g.

It would be understood that various embodiments and configurations and distributions of the components of system 10 across different devices and locations are consistent with practice of the methods described herein. For example, a user may use a handheld embodiment that accepts data from a test subject, and transmits that data across a network connection to another device or location wherein the data is analyzed according to a formulae described herein. A result of such an analysis can be stored at the other location and/or additionally transmitted back to the handheld embodiment. In such a configuration, the act of accepting data from a test subject can include the act of a user inputting the information. The network connection can include a web-based interface to a remote site at, for example, a healthcare provider. Alternatively, system 10 can be a device such as a handheld device that accepts data from the test subject, analyzes the data, such as by inputting the data into a formula as further described herein, and generating a result that is displayed to the user. The result can then be, optionally, transmitted back to a remote location by a network interface such as a wireless interface. System 100 may further be configured to permit a user to transmit by e-mail results of an analysis directly to some other party, such as a healthcare provider, or a diagnostic facility, or a patient.

Kits and Compositions

It will be appreciated that components for practicing the methods described herein may be assembled in a kit.

“Kit” refers to a combination of physical elements, e.g., probes, including without limitation specific primers, labeled nucleic acid probes, antibodies, protein-capture agent(s), reagent(s), instruction sheet(s) and other elements useful to practice the disclosure, in particular to identify the levels of particular RNA molecules in a sample. These physical elements can be arranged in any way suitable for carrying out the disclosure. For example, probes and/or primers can be provided in one or more containers or in an array or microarray device.

In the context of this disclosure, the term “probe” refers to a molecule which can detectably distinguish between target molecules differing in structure, such as allelic variants. Detection can be accomplished in a variety of different ways but preferably is based on detection of specific binding. Examples of such specific binding include antibody binding and nucleic acid probe hybridization.

The present disclosure encompasses the use of diagnostic kits based on a variety of methodologies, e.g., PCR, reverse transcriptase-PCR, quantitative PCR, microarray, chip, mass-spectroscopy, which are capable of detecting RNA levels in a sample. There is also provided an article of manufacturing comprising packaging material and an analytical agent contained within the packaging material, wherein the analytical agent can be used for determining and/or comparing the levels of RNA encoded by one or more target genes of the disclosure, and wherein the packaging material comprises a label or package insert which indicates that the analytical agent can be used to identify levels of RNA that correspond to a probability that a test subject has heart failure, or to the severity of heart failure or to survival outcome, for example, a probability that the test subject has heart failure as opposed to not having heart failure.

Therefore, there is provided kits comprising degenerate primers to amplify polymorphic alleles or variants of target genes of the disclosure, and instructions comprising an amplification protocol and analysis of the results.

The kit may alternatively also comprise buffers, enzymes, and containers for performing the amplification and analysis of the amplification products. The kit may also be a component of a screening or prognostic kit comprising other tools such as DNA microarrays. The kit may also provides one or more control templates, such as nucleic acids isolated from sample of patients without colorectal cancer, and/or nucleic acids isolated from samples of patients with colorectal cancer.

The kit may also include instructions for use of the kit to amplify specific targets on a solid support. Where the kit contains a prepared solid support having a set of primers already fixed on the solid support, e.g. for amplifying a particular set of target polynucleotides, the kit also includes reagents necessary for conducting a PCR on a solid support, for example using an in situ-type or solid phase type PCR procedure where the support is capable of PCR amplification using an in situ-type PCR machine. The PCR reagents, included in the kit, include the usual PCR buffers, a thermostable polymerase (e.g. Taq DNA polymerase), nucleotides (e.g. dNTPs), and other components and labeling molecules (e.g. for direct or indirect labeling). The kits can be assembled to support practice of the PCR amplification method using immobilized primers alone or, alternatively, together with solution phase primers.

In one embodiment, the kit provides one or more primer pairs, each pair capable of amplifying RNA encoded by a target gene of the disclosure, thereby providing a kit for analysis of RNA expression of several different target genes of the disclosure in a biological sample in one reaction or several parallel reactions. Primers in the kits may be labeled, for example fluorescently labeled, to facilitate detection of the amplification products and consequent analysis of the RNA levels.

Examples of amplification techniques include strand displacement amplification, as disclosed in U.S. Pat. No. 5,744,311; transcription-free isothermal amplification, as disclosed in U.S. Pat. No. 6,033,881; repair chain reaction amplification, as disclosed in WO 90/01069; ligase chain reaction amplification, as disclosed in European Patent Appl. 320 308; gap filling ligase chain reaction amplification, as disclosed in U.S. Pat. No. 5,427,930; and RNA transcription-free amplification, as disclosed in U.S. Pat. No. 6,025,134.

In one embodiment, levels of RNA encoded by more than one target gene can be determined in one analysis. A combination kit may therefore include primers capable of amplifying cDNA derived from RNA encoded by different target genes. The primers may be differentially labeled, for example using different fluorescent labels, so as to differentiate between RNA from different target genes.

Multiplex, such as duplex, real-time RT-PCR enables simultaneous quantification of 2 targets in the same reaction, which saves time, reduces costs, and conserves samples. These advantages of multiplex, real-time RT-PCR make the technique well-suited for high-throughput gene expression analysis. Multiplex qPCR assay in a real-time format facilitates quantitative measurements and minimizes the risk of false-negative results. It is essential that multiplex PCR is optimized so that amplicons of all samples are compared insub-plateau phase of PCR. Yun, Z., I. Lewensohn-Fuchs, P. Ljungman, L. Ringholm, J. Jonsson, and J. Albert. 2003. A real-time TaqMan PCR for routine quantitation of cytomegalovirus DNA in crude leukocyte lysates from stem cell transplant patients. J. Virol. Methods 110:73-79. [PubMed]. Yun, Z., I. Lewensohn-Fuchs, P. Ljungman, and A. Vahlne. 2000. Real-time monitoring of cytomegalovirus infections after stem cell transplantation using the TaqMan polymerase chain reaction assays.

Transplantation 69:1733-1736. [PubMed]. Simultaneous quantification of up to 2, 3, 4, 5, 6, 7, and 8 or more targets may be useful.

Accordingly, there is provided a kit comprising packaging and containing, for each gene of a set of one or more of the genes listed in Tables 1, 3, 4, 5, 6, 7 and 8, a primer set capable of generating an amplification product of DNA complementary to RNA encoded, in a human subject, only by the gene.

In another aspect, the kit further comprises a computer-readable medium having instructions stored thereon that are operable when executed by a computer for comparing the test data representing a level of RNA encoded by the gene in blood of a human test subject to a first positive control data representing levels of RNA encoded by the gene in blood of human control subjects having a first categorized severity of heart failure to thereby determine at least one value indicating whether the test data corresponds to the control data, wherein an indication by the at least one value that the test data corresponds to the first positive control data classifies the test subject as having the first categorized severity of heart failure.

In another embodiment, the computer readable medium further has instructions stored thereon that are operable when executed by a computer for comparing a second positive control data representing levels of RNA encoded by the gene in blood of human control subjects having a second categorized severity of heart failure, wherein correspondence between the test data and the second positive control data indicates that the test subject has the second categorized severity of heart failure.

In yet another aspect, there is provided a kit comprising packaging and containing, for each gene of a set of one or more of the genes listed in Tables 1, 3, 4, 5, 6, 7 and 8, a primer set capable of generating an amplification product of DNA complementary to RNA encoded, in a human subject, only by the gene.

In another aspect, the kit further comprises a thermostable polymerase, a reverse transcriptase, deoxynucleotide triphosphates, nucleotide triphosphates and/or enzyme buffer.

In yet another aspect, the kit further comprises at least one labeled probe capable of selectively hybridizing to either a sense or an antisense strand of the amplification product.

In yet another aspect of the disclosure, the kit further contains a computer-readable medium of the disclosure.

In one aspect, the kit is identified in print in or on the packaging as being for determining severity of heart failure in a test subject, for example, a probability that a test subject has a particular heart failure classification as opposed to not having the particular heart failure classification.

In another aspect, the kit is identified in print in or on the packaging as being for monitoring the progression of heart failure in a test subject.

In a further aspect, the kit is identified in print in or on the packaging as being for classifying whether a test subject has decompensated heart failure as opposed to not having heart failure.

In various aspects of the kits described herein, the set of genes may be any combination of two or more of the target genes, as described hereinabove and in the Examples section, below.

The disclosure also provides primer sets, isolated compositions and test systems.

Examples of a primer of the disclosure include an oligonucleotide which is capable of acting as a point of initiation of polynucleotide synthesis along a complementary strand when placed under conditions in which synthesis of a primer extension product which is complementary to a polynucleotide is catalyzed. Such conditions include the presence of four different nucleotide triphosphates or nucleoside analogs and one or more agents for polymerization such as DNA polymerase and/or reverse transcriptase, in an appropriate buffer (“buffer” includes substituents which are cofactors, or which affect pH, ionic strength, etc.), and at a suitable temperature. A primer must be sufficiently long to prime the synthesis of extension products in the presence of an agent for polymerase. A typical primer contains at least about 5 nucleotides in length of a sequence substantially complementary to the target sequence, but somewhat longer primers are preferred.

The terms “complementary” or “complement thereof”, as used herein, refer to sequences of polynucleotides which are capable of forming Watson & Crick base pairing with another specified polynucleotide throughout the entirety of the complementary region. This term is applied to pairs of polynucleotides based solely upon their sequences and does not refer to any specific conditions under which the two polynucleotides would actually bind.

A primer will always contain a sequence substantially complementary to the target sequence, that is the specific sequence to be amplified, to which it can anneal.

A primer which “selectively hybridizes” to a target polynucleotide is a primer which is capable of hybridizing only, or mostly, with a single target polynucleotide in a mixture of polynucleotides consisting of RNA of human blood, or consisting of DNA complementary to RNA of human blood.

Accordingly, there is provided an isolated composition comprising a blood sample from a test subject and, for each gene of one or more of the genes listed in Tables 1, 3, 4, 5, 6, 7 and 8, exogenous nucleic acid selected from the group consisting of: RNA encoded by the gene, cDNA complementary to RNA encoded by the gene, an oligonucleotide which specifically hybridizes to cDNA complementary to RNA encoded by the gene under stringent conditions, an oligonucleotide which specifically hybridizes to RNA encoded by the gene under stringent conditions, a primer set capable of generating an amplification product of cDNA complementary to RNA encoded by the gene, and an amplification product of cDNA complementary to RNA encoded by the gene.

In another embodiment, there is provided an isolated composition comprising, for each gene of a set of one or more of the genes listed in Tables 1, 3, 4, 5, 6, 7 and 8, exogenous nucleic acid which is isolated from a blood sample of a test subject, and which is selected from the group consisting of: RNA encoded by the gene, cDNA complementary to RNA encoded by the gene, an oligonucleotide which specifically hybridizes to cDNA complementary to RNA encoded by the gene under stringent conditions, an oligonucleotide which specifically hybridizes to RNA encoded by the gene under stringent conditions, a primer set capable of generating an amplification product of cDNA complementary to RNA encoded by the gene, and an amplification product of cDNA complementary to RNA encoded by the gene.

In a further aspect, there is provided a test system comprising, for each gene of a set of one or more of the genes listed in Tables 1, 3, 4, 5, 6, 7 and 8; and for each blood sample of a set of blood samples from different subjects: exogenous nucleic acid isolated from the sample selected from the group consisting of RNA encoded by the gene, cDNA complementary to RNA encoded by the gene, an oligonucleotide which specifically hybridizes to cDNA complementary to RNA encoded by the gene under stringent conditions, an oligonucleotide which specifically hybridizes to RNA encoded by the gene under stringent conditions, a primer set capable of generating an amplification product of cDNA complementary to RNA encoded by the gene, and an amplification product of cDNA complementary to RNA encoded by the gene.

The above disclosure generally describes the present disclosure. A more complete understanding can be obtained by reference to the following specific examples. These examples are described solely for the purpose of illustration and are not intended to limit the scope of the disclosure. Changes in form and substitution of equivalents are contemplated as circumstances might suggest or render expedient. Although specific terms have been employed herein, such terms are intended in a descriptive sense and not for purposes of limitation.

The following non-limiting examples are illustrative of the present disclosure:

EXAMPLES Example 1 Material and Methods:

Subject recruitment. Among 97 adults with and without HF, we measured BNP and extracted total RNA from peripheral leukocytes. Microarray hybridization was performed using GeneChip U133Plus2 (Affymetrix) to examine gene expression profiles. The severity of HF was characterized using New York Heart Association (NYHA) classification.

Blood collection, RNA extraction and microarray hybridization. Overnight fasting blood samples were collected using a Vacutainer™ tube and stored on ice till RNA extraction. Blood samples were processed for RNA extraction within six hours after blood collection. Red blood cells were ruptured with hypotonic haemolysis buffer, followed by collection of white blood cells by centrifugation. White blood cell total RNA was extracted with Trizol® Reagent. The quality of RNA samples was assessed on an Agilent Bioanalyzer 2100 using RNA 6000 Nano Chips; the quantity of RNA was measured by UV spectrophotometry. Five microgram of total RNA of each sample was used for hybridization on a GeneChip U133Plus2.

Data analysis. Probe-level expression data were processed by GC-Robust Multichip Analysis (GC-RMA) using GeneSpring v7.3 software. Genes showing unreliable measurements, assessed by cross-gene error model, were removed from any further analysis. Differentially regulated genes between NYHA I-II patients and healthy controls and between NYHA III-IV patients and healthy controls were identified by applying a t-test to the gene expression levels in these experimental groups, and a p value of 0.05 was chosen as the significance cut-off.

Results:

We analyzed gene expression levels in 20 healthy control, 20 NYHA-I, 20 NYHA-II, 30 NYHA-III and 7 NYHA-IV subjects. Overall, 486 genes were found to be differentially expressed (p<0.05) between controls and combined NYHA I-II patients, and between controls and combined NYHA III-IV patients.

Expression levels per subject per gene are shown in Table 1.

Various descriptors for the genes are provided in Table 2.

The genes differentially expressed between controls and NYHA I-II patients are listed and characterized in Table 3. Table 3 provides the maximum overall accuracy of classification power of the genes in terms of receiver-operating characteristic (ROC) area under the curve (AUC), where increasing value indicates increasing accuracy. Table 3 also provides the average fold-change gene expression in NYHA I-II relative to control. The table indicates the threshold fold-change gene expression defining a probability of NYHA I-II as opposed to healthy (sensitivity=0.6). This represents a suitable threshold for classifying a test subject as more likely to have heart failure NYHA I-II than to be healthy. The table further indicates the extreme fold-change relative to average of controls observed in a NYHA I-II sample. This extreme can serve to limit a range of fold-change expression which classifies a test subject as probably having heart failure NYHA I-II rather than being healthy. The table further indicates the threshold fold-change gene expression defining a probability of healthy as opposed to NYHA I-II (specificity=0.6). This represents a suitable threshold for classifying a test subject as more likely to be healthy than to have heart failure NYHA I-II. The table further indicates the extreme fold-change relative to average of controls observed in a control sample. This extreme can serve to limit a range of fold-change expression which classifies a test subject as probably being healthy rather than having heart failure NYHA I-II.

The genes differentially expressed between controls and NYHA III-IV patients are listed and characterized in Table 4. Table 4 provides the maximum overall accuracy of classification power of the genes in terms of receiver-operating characteristic (ROC) area under the curve (AUC), where increasing value indicates increasing accuracy. Table 4 also provides the average fold-change gene expression in NYHA III-IV relative to control. The table indicates the threshold fold-change gene expression defining a probability of NYHA III-IV as opposed to healthy (sensitivity=0.6). This represents a suitable threshold for classifying a test subject as more likely to have heart failure NYHA III-IV than to be healthy. The table further indicates the extreme fold-change relative to average of controls observed in a NYHA III-IV sample. This extreme can serve to limit a range of fold-change expression which classifies a test subject as probably having heart failure NYHA III-IV rather than being healthy. The table further indicates the threshold fold-change gene expression defining a probability of healthy as opposed to NYHA III-IV (specificity=0.6). This represents a suitable threshold for classifying a test subject as more likely to be healthy than to have heart failure NYHA III-IV. The table further indicates the extreme fold-change relative to average of controls observed in a control sample. This extreme can serve to limit a range of fold-change expression which classifies a test subject as probably being healthy rather than having heart failure NYHA III-IV.

The genes displaying a trend of increased fold-change expression relative to controls as a function of severity are listed and described in Table 5, which displays average fold-change expression side-by-side for NYHA I-II and NYHA III-IV.

The genes displaying increased average fold-change expression in NYHA I-II and less increased average fold-change expression in NYHA III-IV, relative to controls, are listed and described in Table 6, which displays average fold-change expression side-by-side for NYHA I-II and NYHA III-IV.

The genes displaying a trend of decreased fold-change expression relative to controls as a function of severity are listed and described in Table 7, which displays average fold-change expression side-by-side for NYHA I-II and NYHA III-IV.

The genes displaying decreased average fold-change expression in NYHA I-II and less decreased average fold-change expression in NYHA III-IV, relative to controls, are listed and described in Table 8, which displays average fold-change expression side-by-side for NYHA I-II and NYHA III-IV.

Example 2 Classification of a Patient Suspected of Potentially Having Heart Failure in Relation to a Likelihood of Having NYHA I-II Stage Heart Failure, Having NYHA III-IV Stage Heart Failure or not Having Heart Failure

Overnight fasting blood samples are collected using Vacutainer™ tubes from a patient suspected of potentially having heart failure and from 20 healthy control subjects, and the samples are stored on ice until RNA extraction. The blood samples are processed for RNA extraction within six hours after blood collection. Red blood cells are ruptured with hypotonic haemolysis buffer, followed by collection of white blood cells by centrifugation. White blood cell total RNA samples are extracted with Trizol® Reagent. The quality of the RNA samples is confirmed on an Agilent Bioanalyzer 2100 using RNA 6000 Nano Chips; and the quantity of RNA in the samples is measured by UV spectrophotometry. Five micrograms of total RNA per sample is used to generate cDNA for hybridization on a GeneChip U133Plus2 according to the manufacturer's instructions to determine the level of RNA encoded by the genes SRP14 and GIMAP1 in the sample from the test subject and to determine the average level of RNA encoded by these genes in the samples from the control subjects.

The ratio of the level of RNA encoded by SRP14 in the sample from the patient to the average level of RNA encoded by SRP14 in the blood samples of the healthy subjects is determined, and the ratio of the level of RNA encoded by GIMAP1 in the sample from the patient to the average level of RNA encoded by GIMAP1 in the blood samples of the healthy subjects is determined.

The patient is classified as more likely to have NYHA I/II stage heart failure than to either be healthy or to have NYHA III/IV stage heart failure if the level of RNA encoded by SRP14 in the sample from the patient is 1.062 to 1.268 fold of the average level of RNA encoded by the gene in the blood samples of the healthy subjects.

Alternately, the patient is classified as more likely to have NYHA III/IV stage heart failure than to either be healthy or have NYHA I/II stage heart failure if the level of RNA encoded by GIMAP1 in the sample from the patient is between 0.945 and 0.543 fold of the average level of RNA encoded by the gene in the blood samples of the healthy subjects.

While the present disclosure has been described with reference to what are presently considered to be the preferred examples, it is to be understood that the disclosure is not limited to the disclosed examples. To the contrary, the disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

All publications, patents and patent applications are herein incorporated by reference in their entirety to the same extent as if each individual publication, patent or patent application was specifically and individually indicated to be incorporated by reference in its entirety.

TABLE 1 Control Control Control Control Control Control Control Control Control Control Control Affymetrix Probe Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample set ID Gene symbol no. 0 no. 1 no. 2 no. 3 no. 4 no. 5 no. 6 no. 7 no. 8 no. 9 no. 10 1552318_at GIMAP1 1884 1485 1803 1449 1283 1458 1227 1331 1418 1227 2513 1552630_a_at SRCAP 124.2 77.98 83.1 111.6 119.3 81.48 89.83 121.9 112.1 94.63 85.48 1554149_at CLDND1 966.2 670.3 919.9 648.5 660.5 805.4 696.9 545.5 647 587.6 858.2 1554539_a_at RHOF 119.6 72.46 104.7 70.66 84.17 78.23 74.03 93.15 111.3 64.01 114 1554606_at CCDC100 168.1 139.9 169.3 136.5 166.1 173.2 128.5 147.2 169.3 76.54 170.7 1555630_a_at RAB34 198 120.9 71.23 147.2 172.7 117.2 69.16 90.66 84.27 128.9 97.02 1555963_x_at B3GNT7 35.32 46.43 47.27 31.58 35.36 39.48 47.66 32.43 48.2 30.38 33.7 1555996_s_at EIF4A2 1295 828.9 1099 889.6 1060 1383 701.3 893 1166 802.1 1461 1556113_at DKFZp451A211 29.92 32.62 39.7 39.32 33.56 38.93 26.64 39.37 37.71 47.7 37.74 1556283_s_at FGFR1OP2 165 131.2 76.38 88.58 109.6 91.5 78.85 65.81 92.95 102.7 102.4 1556864_at TECT1 39.23 57.48 47.99 50.52 56.56 52.86 46.94 69.12 45.4 73.37 46.87 1557066_at LUC7L 245.7 204 185.9 187.3 200.9 175.5 172.4 136.3 187.1 107.9 247.5 1558277_at ZNF740 28.41 29.88 40.89 38.67 48.19 21.6 28.24 29.86 40.84 28.75 28.62 1558755_x_at ZNF763 205.3 220.2 180.7 179.7 89.79 150.6 150.4 211.1 123.7 201.4 221.1 1561146_at VPS35 92.5 58.25 83.94 93.63 60.41 65.66 84.88 77.47 67.39 61.95 70.71 1564962_at ZNF92 60.78 30.12 36.82 45.16 35.55 44.63 34.07 36.45 37.79 36.78 55.12 1567013_at NFE2L2 92.13 116.1 99.01 96.95 90.98 100.3 148.1 102.5 95.55 98.68 97.62 1568815_a_at DDX50 151 131.3 166.8 174.3 131.9 131.7 334.3 130.7 133.7 105.5 170 200007_at SRP14 7803 7464 6882 7173 7378 7689 7067 6304 7925 6829 7844 200010_at RPL11 13172 11186 13349 12281 12038 12587 12238 10770 11718 11894 15543 200059_s_at RHOA 9515 10294 9906 9957 9308 9998 10117 9804 8995 10155 9330 200091_s_at RPS25 26796 19506 20137 21044 22753 21927 21649 18680 20566 18754 27490 200633_at UBB 8209 7467 10589 8228 7630 7988 7521 7384 8521 6871 9354 200650_s_at LDHA 5717 3812 6061 4920 4228 5319 4170 4601 5985 5270 4737 200672_x_at SPTBN1 157.4 210 160.2 181.6 210.4 161.8 159.3 134.5 145.9 110.6 227.3 200677_at PTTG1IP 2484 2759 2222 2605 2859 3023 2457 2577 2249 2634 2290 200713_s_at MAPRE1 1308 1366 1543 1430 1561 1322 1411 1259 1340 1313 1286 200822_x_at TPI1 1372 1229 1263 1184 1134 1187 1204 1089 870.8 1123 1084 200829_x_at ZNF207 571.7 461.4 573.6 552.4 506.3 567.8 482 437.8 539.9 448.2 546.1 200839_s_at CTSB 2846 2379 3032 2892 2294 2354 1816 2157 2522 2355 2562 200932_s_at DCTN2 454 435.5 472.1 414 458.4 460.7 396 402.9 477.2 462.2 453.6 200950_at ARPC1A 472.4 452.8 476.3 501.2 495.3 505.8 493.2 468.7 478.5 483 528.9 201031_s_at HNRPH1 9510 8383 9288 9897 8687 9842 6879 7563 8735 8125 11125 201075_s_at SMARCC1 433 323.1 328.6 354.4 396.8 401.7 318.8 368 326.9 319 348.4 201098_at COPB2 770.5 715.6 713.1 759.7 839 761.4 723.4 681.7 718.9 679.4 709.7 201105_at LGALS1 4549 2137 2378 1646 3209 2769 1484 2191 3612 2985 2061 201172_x_at ATP6V0E1 2863 3706 3694 3320 3105 3193 3483 3115 3287 3165 3017 201186_at LRPAP1 466.4 436.1 398.8 543.2 485.1 436.2 622 459.7 422.8 551.5 365.9 201193_at IDH1 550.4 448.8 557.1 578.6 482.4 510.1 435.7 453.8 445.4 560.4 385.5 201198_s_at PSMD1 146.9 166.2 165.9 134.5 133.8 176.9 110 126.9 122.1 144.9 168.5 201220_x_at CTBP2 1408 1473 1391 1441 1634 1719 1749 1634 1252 1542 1330 201234_at ILK 1080 1143 987 1398 1211 1090 1278 1191 1135 1033 1076 201357_s_at SF3A1 398.2 392.7 427.4 395.6 384.7 422.7 510.4 499.4 383.6 384.1 358.3 201363_s_at IVNS1ABP 1579 1414 1439 1935 1780 1977 1530 2257 1550 1762 1658 201400_at PSMB3 1346 1795 1744 1704 1581 1540 1603 1551 1618 1594 1622 201421_s_at WDR77 197.9 167.8 160.4 171 185.1 189.7 121.3 127.1 144.7 132.9 209.5 201422_at IFI30 8577 5701 5628 8420 6716 7306 6399 6907 7570 6983 5692 201426_s_at VIM 14865 12674 15376 14013 15626 15301 13339 14124 14113 15027 13339 201453_x_at RHEB 1240 1281 1396 1284 1124 1227 1199 1104 1202 1240 1207 201470_at GSTO1 1302 1060 987.9 1182 1357 1082 927.3 883.4 999.3 985.2 1047 201478_s_at DKC1 319.3 276.2 302.1 275.8 254.7 346.3 254.8 267.3 240.4 234.8 307.3 201527_at ATP6V1F 929.3 799.4 943.7 901.1 767.1 765.6 819 720.7 801.9 762.1 831 201536_at DUSP3 389 259.2 262.1 388.2 240.7 424.4 377.4 312.1 355 279.2 285.9 201554_x_at GYG1 726.8 485.7 694.8 607.8 650 871.6 921.5 761.7 702 750.5 642.5 201556_s_at VAMP2 549.2 785.7 592.5 651.3 857.5 1020 819.9 1082 665.3 720.2 708.5 201576_s_at GLB1 731.9 574.3 537 668.6 738.8 591 630.1 509.6 500.9 620.3 561.5 201590_x_at ANXA2 3505 2218 2522 3501 2525 2955 1744 2093 3041 3073 2371 201628_s_at RRAGA 614.4 563.7 731 525.5 550.3 564.9 614.7 555.1 482.4 498 592.8 201788_at DDX42 543.2 548.9 600.5 596.7 543.2 699.2 578.8 488.4 467.4 535.4 740.8 201900_s_at AKR1A1 472 356.7 394.3 502.1 373.9 414.2 368.3 331.2 344.2 302.7 476.8 201945_at FURIN 447.7 569.8 369.2 511.9 526.5 508.8 784.3 734.7 415 586.2 384.2 202068_s_at LDLR 92.13 65.16 70.79 66.81 65.9 120.2 31.58 75.07 120.9 90 56.49 202104_s_at SPG7 442.8 474.9 476.1 436 476.8 389.1 389 429.9 405.3 335.4 501.6 202138_x_at JTV1 296.5 246.8 280.5 258.9 249.1 291 200.5 206.3 238.7 217.7 268.2 202185_at PLOD3 221.7 179.2 213.7 199.9 194 199.6 183.5 185.9 186.4 185.2 191.7 202192_s_at GAS7 576.8 526.7 509.3 506.2 905.7 761.2 650.3 615.2 498 580.8 427.1 202201_at BLVRB 740.8 493.2 380 541.5 494.6 493.7 391.4 388.5 476.7 673.1 385.8 202249_s_at WDR42A 243.1 258.7 231.2 227.1 295.3 254.5 245.7 265.7 210 217 237.9 202252_at RAB13 97.44 91.77 83.75 67.72 88.48 100.5 99.67 81.18 60.81 68.19 62.37 202262_x_at DDAH2 76 72.47 74.23 75.14 74.95 128.2 124.3 73.46 107.9 84.68 83.94 202380_s_at NKTR 654.8 681.6 773.4 676.8 653.4 775.9 618.4 556.1 561.7 537.2 809.7 202381_at ADAM9 520 315.1 307.6 447.8 513.7 403.8 354.3 344.2 382.5 456.7 285.8 202428_x_at DBI 2216 1652 2182 1824 1911 2206 1723 1640 1958 1784 1845 202445_s_at NOTCH2 198 151.4 131.7 156.5 160.8 199.1 192.9 148.2 140.6 174.5 180.5 202461_at EIF2B2 183.7 156.4 190.1 175 142.9 146.6 166.5 107.2 174.5 115.7 181.2 202522_at PITPNB 628.5 643.8 744.3 586.9 542.4 602.8 662.8 593.1 659.3 608.1 652.9 202523_s_at SPOCK2 332.9 173.9 308.5 233.3 230.4 128.7 338.5 289.7 228.9 147.8 363.2 202594_at LEPROTL1 874.2 932.8 1043 981.2 1125 1079 853.2 973.3 1125 944.6 1178 202623_at EAPP 1279 1179 1458 1193 1321 1261 1106 1324 1130 1158 1358 202652_at APBB1 41.64 44.49 52.08 40.68 35.16 38.92 53.9 34.51 30.56 35.42 59.96 202724_s_at FOXO1 483.5 550.6 529.3 520.9 668 509.1 603.7 527.8 481.3 469 691.6 202750_s_at TFIP11 182 206.2 163.7 216.8 144.8 143.9 212.3 178.5 194.2 158.1 141.7 202778_s_at ZMYM2 604.5 591.3 560.5 603 704.5 664.6 624.1 630.5 518.6 636.8 588.5 202910_s_at CD97 3345 3649 3145 2997 3996 2526 4236 3286 3749 3867 3215 202928_s_at PHF1 139.9 145.8 182.7 152.5 161 157.8 224.7 198.1 160.6 134.1 197.5 202944_at NAGA 515 399.7 357.4 465.7 351.4 322.1 271.8 270.5 287.1 301.4 333.1 202979_s_at CREBZF 949.8 698.7 844.5 660.7 812.7 824.6 575.3 703.6 801.8 547.4 1067 203003_at MEF2D 113.2 135.8 105.5 100.3 127.4 124.7 147.9 162.1 99.28 99.52 98.68 203127_s_at SPTLC2 307.8 319.7 226.1 306.8 343.6 307.8 301.8 267.3 295 325.7 218.6 203137_at WTAP 1897 1665 2024 2093 1891 1662 1646 1822 1959 2138 2200 203184_at FBN2 151.9 49.68 84.2 106.8 147.1 32.88 55.32 85.65 74.35 69.59 56.49 203234_at UPP1 388.9 326.2 279.8 440.3 466.9 608.6 476.5 355.6 399.9 622.8 338.8 203278_s_at PHF21A 702 941.7 832.3 865 1069 941.5 1318 1041 1065 1066 744.5 203305_at F13A1 1003 1052 767.7 1494 896.7 773.6 898.1 713.8 853.8 1129 556 203371_s_at NDUFB3 978.5 895.1 1118 933.4 1227 1244 1317 1050 1441 1258 962.6 203413_at NELL2 514.7 462.8 574.3 523.8 502.5 542.4 619.7 302.9 285.1 331.6 1007 203416_at CD53 9075 10473 11266 9781 9328 9796 10223 9767 10527 10381 9523 203492_x_at CEP57 255.2 213.2 334.3 235.9 251.8 295.5 232.3 230.5 280.7 209.5 268.5 203534_at LSM1 957.3 683.1 800.8 741.7 716.9 744.3 722.1 593.6 664.2 597 756.6 203535_at S100A9 32414 38070 34471 39800 39980 40296 41494 41371 38393 42593 35664 203578_s_at SLC7A6 161.3 100.3 102.6 112.6 149.9 149.4 104.2 74.93 114.6 115.4 169.9 203748_x_at RBMS1 1231 1426 1752 1462 1464 1617 1787 1526 1398 1419 1510 203759_at ST3GAL4 87.89 119.9 71.37 91.81 126.7 144 124.2 134.5 114.8 187.5 113.1 203844_at VHL 26.5 26.2 29.07 28.16 24.76 27.35 25.39 27.79 25.14 30.34 25.97 203880_at COX17 283 216.7 227.8 254.5 274.6 336.9 206.9 175.3 245.1 211.4 245 203912_s_at DNASE1L1 276.8 188.2 121.3 174 188.5 195.7 207.6 138.1 139.9 135.5 191.9 203939_at NT5E 83.05 95.94 84.68 58.85 159.3 80.49 87.63 58.04 84.08 58.25 111.1 203971_at SLC31A1 139.6 115.6 124.6 88.98 138.7 106.9 80.79 85.82 116.9 98.68 65.59 204050_s_at CLTA 1522 1130 1257 1265 1150 1156 1058 1038 1023 1129 1141 204068_at STK3 88.34 100.1 52.55 96.49 101.1 106.1 105 73.45 82.14 93.91 66.86 204099_at SMARCD3 134.2 124.8 100.4 173.3 152.4 134.5 148 115.2 169.8 171.1 131.1 204143_s_at ENOSF1 172.1 156.7 235.1 160.7 202.2 243.3 156 138.1 178.8 103.6 388.6 204204_at SLC31A2 1991 2514 1765 1191 2508 2226 2037 1660 2072 2162 1118 204214_s_at RAB32 560.9 457 465.9 638.8 589.7 492.6 454.6 503.2 460.7 668 448.3 204232_at FCER1G 4642 2846 2860 3236 4318 4339 4376 2374 3723 4488 3376 204243_at RLF 213.5 262.3 212.4 228.8 277.5 262.2 268.9 192.2 201.6 304.8 199.8 204249_s_at LMO2 2407 2898 2281 3756 2770 2701 2172 2244 3530 2445 2131 204291_at ZNF518 542.4 464.7 365 553.6 559.3 537.8 375.7 460.2 496.3 577 499.4 204342_at SLC25A24 912.5 588.1 743.9 780.1 730.4 697.8 634.3 637 980 664.8 726 204352_at TRAF5 448.8 420.9 757 373.3 482.9 437.1 474.9 294.3 387.7 260.6 970.6 204401_at KCNN4 185.6 87.25 123.8 142.6 126.9 154.3 149.4 141.1 155.7 146 257.7 204504_s_at HIRIP3 97.43 82.43 121.3 107.6 100.9 108.5 90.48 107.5 96.97 107.4 116.2 204617_s_at ACD 329.5 366 348.1 310.7 341.2 297.1 370 345.7 255.9 276.8 403.6 204645_at CCNT2 1144 931.3 965.3 984.8 1072 970.4 832.8 992.2 1211 994.6 1001 204675_at SRD5A1 108.7 59.78 72.44 120 105.5 99.38 72.63 49.66 92.48 82.93 92.22 204689_at HHEX 472.7 428.7 440 498.2 534.6 495.4 457.6 397.8 516.3 487.9 500.4 204801_s_at DHRS12 49.68 30.65 29.64 44.71 45.49 49.3 35.44 52.97 36.63 73.82 34.85 205235_s_at MPHOSPH1 97.85 80.02 99.73 99.65 80.41 110.5 98.97 95.75 85.52 87.1 113.4 205254_x_at TCF7 372.8 311.1 358.6 364.6 353.2 256.9 432.6 301.6 198.3 230.3 576.8 205256_at ZBTB39 65.34 64.65 97.14 68.87 62.88 67.57 64.98 74.04 72.97 66.53 85.45 205322_s_at MTF1 422.7 475.2 505.2 534.4 494.4 528.8 654.3 498.5 488.4 570.4 390.2 205340_at ZBTB24 140.6 116.2 140 155.5 139 152.8 110.1 114.6 140.4 134.1 184.9 205349_at GNA15 212.1 170.6 118.4 170 160.1 169.3 125.1 116.3 159.5 177.8 117.3 205550_s_at BRE 252.4 260.9 270.3 232.6 225.3 269.8 266.7 212.5 254.3 270.3 254.3 205811_at POLG2 167.8 184.9 182.4 163 163.1 193.2 133.3 132.7 163.1 158.7 200.9 205835_s_at YTHDC2 138.9 96.7 113.2 142.3 144.8 113.2 82.04 112 121.3 80.94 138.9 205895_s_at NOLC1 169.2 120.2 218.6 148.4 157.7 198.5 129.5 137.8 175.7 120.1 187.8 205965_at BATF 185.3 152.5 152.1 157.8 152.4 211.1 180.4 188.5 228.1 158.6 158.2 205976_at FASTKD2 81.82 53.03 65.27 46.09 56.8 40.62 24.57 39.13 54.67 44.27 78.2 206015_s_at FOXJ3 687.5 687.2 771.9 715.9 768.6 762.9 707.2 615.2 615.6 652.6 745.8 206037_at CCBL1 31.53 35.72 35.23 39.58 48.94 35.84 44.4 38.17 27.4 43.83 40.81 206170_at ADRB2 220.1 216 275.4 241.7 128.1 227.3 252.7 135.5 270.3 161.6 199.9 206182_at ZNF134 132.1 101.6 142.7 117.7 86.07 101.8 119.9 98.54 109.2 116.2 149 206343_s_at NRG1 19.31 16.48 26.29 26.52 16.33 15.73 8.638 12.58 6.16 34.29 35.78 206542_s_at SMARCA2 1343 1311 1440 1414 1494 1727 1304 1351 1382 1333 1458 206580_s_at EFEMP2 43.2 73.33 51.21 50.99 57.73 69.74 57.57 55.21 48.92 46.15 57.79 206715_at TFEC 294 205.5 257.8 395.5 266.3 218 157.6 214 299.3 264.6 208.9 206834_at HBD 87.7 68.45 142.6 25.14 27.87 55.14 44.46 54.27 59.38 47.65 76.77 206968_s_at NFRKB 122.4 105.6 106.3 117.7 109.6 113.7 112.3 121.9 99.67 83.69 140.5 207075_at NLRP3 108.8 222.8 186.7 171.7 93.71 130.3 123.3 88.53 109.7 144 104.2 207078_at MED6 202.3 197.3 162.5 200 193.2 165.6 176.5 201.5 198.3 175.2 231 207113_s_at TNF 106.6 97.96 106.3 142.2 124.1 138.8 122.5 68.63 73.1 130 73.92 207164_s_at ZNF238 712.5 743.5 687 798 875.6 956.6 943.9 1033 794.9 683.6 772.5 207233_s_at MITF 99.13 75.94 90.11 115.9 100.8 147.1 93.15 73.52 76.8 84.03 72.91 207416_s_at NFATC3 285.4 265.3 219.7 223.5 254.3 308.7 272.2 270 264.6 227.8 279 207513_s_at ZNF189 259.5 231.2 230.4 345.5 296.6 276.2 223.3 257.5 268.7 300.4 244.8 207543_s_at P4HA1 293.5 321.7 311.1 278.3 379.6 277.1 287.1 239.5 220.1 288.2 239.3 207564_x_at OGT 4664 3833 4140 3397 3937 4971 3338 3250 3386 2734 3672 207971_s_at CEP68 81.87 60.57 77.85 75.24 77.25 85.17 76.71 59.46 62.71 85.75 160.5 208104_s_at TSC22D4 488.4 563.3 534.8 584.3 556.5 455.6 615.6 578.5 503.8 460.3 441.7 208121_s_at PTPRO 66.19 48.45 69.74 122.1 102.5 99.4 45.93 49.13 102 84.75 120.8 208161_s_at ABCC3 44.41 31.25 33.43 47.48 46.39 36.23 42.6 28.55 26.91 26.73 31.67 208269_s_at ADAM28 126 123.3 109.8 132.1 137.1 102.8 99.91 146.1 101.4 105.3 127 208309_s_at MALT1 411.7 238.3 478 329.5 359.5 344.7 266.2 214.5 276.3 175.1 410.6 208527_x_at HIST1H2BE 288.4 336 295.7 410.2 322.8 331.7 325.2 402.8 332 342.1 307.7 208579_x_at H2BFS 540.8 577.4 463.8 710.7 528.1 490.1 471.6 696.6 552.9 437.5 485.7 208635_x_at NACA 16908 13017 15899 15015 14149 15765 13172 12893 13397 12842 17082 208659_at CLIC1 6182 6300 5867 6118 5982 6380 6825 6138 6354 7264 6422 208680_at PRDX1 729.8 440.6 653.9 741.3 627.1 642 474.6 418.4 634.3 543.8 633.9 208749_x_at FLOT1 1413 1857 1570 2312 2029 2258 2835 2615 1938 1972 1812 208771_s_at LTA4H 3764 4934 6635 4440 3590 5490 4104 3410 2630 5528 4454 208780_x_at VAPA 2057 3024 2172 1934 2071 1985 2581 2006 1681 2752 2043 208798_x_at GOLGA8A 1464 1409 1903 1140 1165 1355 1508 1566 867.7 945.9 2556 208805_at PSMA6 1993 1656 1975 2009 1668 1823 1615 1646 2110 1700 1903 208868_s_at GABARAPL1 913.4 1005 839.3 892.6 717.5 988.5 780.9 999.3 924.4 899.7 745.8 208903_at RPS28 70.34 47.85 54.63 63.26 58.99 58.34 62.19 49.35 54.75 48.03 73.69 208921_s_at SRI 1093 874 1129 1037 985.2 1169 1003 893.1 990.9 983.7 1082 208923_at CYFIP1 700.2 399.6 459 620.9 539.1 511 348.3 350 402.6 458.5 389.5 208946_s_at BECN1 1704 1464 1551 1527 1431 1497 1501 1501 1629 1557 1581 208962_s_at FADS1 109.6 64.28 54.07 99.03 44.5 111.6 48.3 43.67 45.12 68.83 48.87 209040_s_at PSMB8 1457 1514 1566 1956 1477 1637 1635 1545 2117 1562 1750 209067_s_at HNRPDL 4005 2347 3383 2939 2872 3247 2614 2327 2692 2202 3765 209072_at MBP 37.16 51.18 77.16 31.27 50.34 61.52 84.23 64.13 32.45 46.78 38.94 209099_x_at JAG1 95.89 73.92 63.36 95.47 136.8 84.27 88.18 94.24 85.67 100.1 82.95 209124_at MYD88 4489 4799 4612 4879 4778 5024 4884 4477 5444 5588 4670 209180_at RABGGTB 406.4 245.9 314.4 329.7 345.1 369.1 244.9 253.1 332.9 270.2 435.9 209191_at TUBB6 166.7 71.68 101.3 80.38 139.6 138.5 73.29 156.8 128 112.8 98.06 209212_s_at KLF5 29.25 23.92 30.18 28.58 29.18 30 29.72 30.03 20.3 31.09 29.76 209218_at SQLE 176.4 80.67 121.8 124.5 86.02 135.6 63.61 66.58 152.7 115.5 115.2 209236_at SLC23A2 231.3 214.6 250.7 244.8 222.4 232.1 192.3 210 166 234.2 244.5 209251_x_at TUBA1C 3893 4739 5131 4801 3980 5196 4839 4364 3776 4907 3867 209259_s_at SMC3 668.6 619.8 508.1 607.8 666.9 648.8 560.8 550.9 500.1 490.6 687.4 209269_s_at SYK 750.8 708.5 504.7 728.6 729 727.8 681.7 1138 507.9 740.7 608.1 209330_s_at HNRPD 3827 2384 2654 2608 3115 2736 1983 2366 2640 2352 3250 209339_at SIAH2 416.3 389 389.9 387.3 415.3 419 450.3 313.6 440.7 361.4 344 209430_at BTAF1 996.1 816.4 1103 878.3 835.6 790.6 736 703.4 771.5 761.8 1049 209675_s_at HNRPUL1 1615 1133 1149 1209 1353 1146 1495 1321 1047 988.9 1205 209684_at RIN2 521.9 256.4 216.7 488.3 382.3 301.8 229.7 225.9 401.5 372.1 225.7 209806_at HIST1H2BK 1789 1497 1274 2351 1674 1314 1473 2321 1910 1385 1320 209840_s_at LRRN3 49.34 126.4 56.07 32.72 42.74 100.7 216.8 6.376 13.1 187.9 173.1 209870_s_at APBA2 130.4 230.7 226.5 178.2 173.4 204.3 165.5 163.6 230.5 182.9 286.4 209892_at FUT4 75.81 69.48 93.03 109.5 88.04 78.17 68.41 54.59 58.72 69.84 63.03 209906_at C3AR1 644.8 339.3 396.8 584.3 586.4 580.4 367.8 460.2 1007 487 311.3 210022_at PCGF1 176.6 156.4 181.5 185.3 229 178.1 179 203.1 166.6 189.2 175.2 210061_at ZNF589 171.7 111.6 110.4 154.9 96.49 91.36 142.2 115.1 111.7 108.9 146.3 210145_at PLA2G4A 73.82 43.97 41.29 89.09 59.06 68.56 64.85 38.8 42.24 51.64 53.14 210156_s_at PCMT1 1108 894 979.2 1144 993.2 1102 851 908.9 1200 1084 949.5 210166_at TLR5 336.3 391.3 355.8 422.1 532.7 569.1 628.8 423.7 389.9 436.6 400.3 210434_x_at JTB 1954 2209 2648 2296 1971 2157 2341 2142 2133 2178 2150 210644_s_at LAIR1 589.2 468.5 394.8 463.6 378.8 379.8 360.9 284.8 290.2 427.5 431.8 210648_x_at SNX3 3250 3348 3886 2986 3126 3173 3301 2834 2977 3319 3140 210875_s_at ZEB1 246.4 205.4 217 260.5 306.9 307.7 312.8 392.4 245.5 235.4 268.4 211047_x_at AP2S1 1194 1018 1183 1252 1032 1095 827.7 896.3 981.5 1029 971.2 211058_x_at TUBA1B 4583 4409 5040 4623 4038 5091 4623 4452 4300 4795 4480 211185_s_at SF3B1 8756 8290 9641 8488 8730 7648 8383 8227 7461 8508 8558 211272_s_at DGKA 579.2 539.1 711.4 764.4 687.6 539.8 690.7 557.2 413.1 478 1109 211323_s_at ITPR1 209.7 141.4 230.1 182.1 183.4 188.8 139.6 159.7 183.6 127.9 182.5 211383_s_at WDR37 407.1 390.3 477.7 433.4 400.5 496 472.4 385.8 372.1 398.9 492.4 211429_s_at SERPINA1 14493 15121 14694 15949 15340 17935 16250 15660 15688 17603 13784 211506_s_at IL8 682.6 826.9 365.6 1706 1594 830.3 1226 827.1 212.5 891 697.7 211546_x_at SNCA 218.8 158.5 201 232 179.2 196.8 160.4 158.4 180.8 161.3 130.8 211684_s_at DYNC1I2 741.4 467.2 610.4 533.6 532.7 496.3 457.2 341.5 445.2 448.8 552.4 211729_x_at BLVRA 469.8 292.5 337.3 582.4 392.2 396 320.5 227.3 495.3 364.7 279.7 211856_x_at CD28 106.3 29.24 82.9 103.9 93.14 98.08 65.92 56.75 88.44 56.52 137.2 211946_s_at BAT2D1 5110 5060 4852 5421 5347 5093 5199 4762 4581 4698 5303 211965_at ZFP36L1 2246 2507 2246 2315 3602 4714 5169 3756 1860 1907 2137 212030_at RBM25 1239 1076 1347 1253 1288 1438 1146 1188 1088 1145 1588 212042_x_at hCG_31916///RPL7 24503 23259 23168 24307 25351 26482 22892 20974 23411 23782 27173 212132_at LSM14A 2999 2839 2691 3235 3421 3142 2881 3046 3115 2969 3688 212213_x_at OPA1 202.2 162 187.7 189.7 206.9 209.4 188.5 169.3 174.7 181.8 223.5 212299_at NEK9 330 328.8 434.2 320.7 331.4 314.5 322.7 234.2 291 253.7 403.6 212331_at RBL2 3174 3533 3901 2963 3999 3111 3209 3637 3275 3414 4127 212334_at GNS 3124 1857 1973 2553 1968 2066 1816 1778 2122 2175 1727 212406_s_at PCMTD2 1349 1254 1346 1412 1553 1399 1274 1265 1059 729.6 1565 212455_at YTHDC1 3281 3126 3517 3372 3557 3517 3506 3379 3635 3389 3604 212543_at AIM1 1030 1185 1357 1225 1144 1264 1057 1172 968.1 1020 1204 212658_at LHFPL2 93.15 72.02 58.78 125.8 77.28 78.88 55.19 79.35 122.4 81.61 56.62 212663_at FKBP15 1313 1124 1224 1324 1324 1205 1085 1191 1062 1267 1014 212769_at TLE3 330.3 483.2 363.3 423 513.7 352.1 639.8 509.5 407.5 527.5 476.2 212820_at DMXL2 1997 2047 1959 2279 2651 2033 2097 2315 2156 1986 1648 212932_at RAB3GAP1 148.4 125.6 119.3 165.9 119.1 194.2 174.7 135.6 126 156.9 178.4 212989_at SGMS1 369.8 418.3 326.1 457.3 358.5 314.2 500.1 330.8 443.3 357.3 367.5 212997_s_at TLK2 583.5 693.7 628.4 651.8 724.4 670.8 693.9 688.6 666.7 697.2 702.1 213021_at GOSR1 281.7 246.4 230.4 267.9 239.2 266.2 209.9 208.9 270.8 253.9 272.2 213152_s_at SFRS2B 751.1 426.9 655.3 479.1 478.3 525.4 447.6 402.4 497.8 383.5 790 213205_s_at RAD54L2 126.8 102.4 163 155.2 163.4 179.2 138.8 151.9 140.2 146.4 168.5 213218_at ZNF187 85.32 88.98 105.6 106.4 89.49 123.6 98.54 127.8 102.7 75.13 121.6 213266_at 76P 85.99 79.27 102.1 56.1 102.8 117.3 88.13 95.62 82.97 72.34 94.54 213302_at PFAS 39.96 40.25 36.15 55.37 43.59 33.97 32.35 19.03 40.8 24.97 67.23 213335_s_at ST3GAL6 29.73 33.49 32.47 40.74 31.78 30.62 32.94 30.7 26.81 34.18 25.07 213397_x_at RNASE4 93.21 116.3 93.89 90.71 54.61 59.9 66.33 37.77 55.72 67.15 57.34 213459_at RPL37A 138.6 141 104.9 88.49 89.02 86.48 97.81 78.25 109.9 75.72 115 213494_s_at YY1 38.41 45.25 31.88 32.97 32.93 51.79 44.14 35.01 32.96 33.74 66.77 213540_at HSD17B8 65.52 52.42 71.07 68.56 59.91 73.82 72.61 52.89 63.74 61.2 83.82 213693_s_at MUC1 36.02 36.37 37.92 36.54 36.75 36.39 36.42 37.32 36.99 37.65 36.2 213827_at SNX26 77.74 58.98 50.07 78.6 69.92 83.08 64.48 69.77 79.02 69.21 73.07 213877_x_at TCEB2 108.6 93.89 103.5 105.8 95.58 89.67 89.05 112.9 104.2 104.6 104.6 214045_at LIAS 91.65 68.63 46.25 60.91 73.65 55.06 40.12 49.81 48.02 57.12 85.72 214057_at MCL1 175.5 234.2 190.7 198.9 204.2 170.7 245.1 233.2 213.3 216.5 261 214330_at ATPAF2 57.12 29.59 50.49 68.06 45.6 41.64 40.86 53.38 55.62 44.58 40.34 214364_at MTERFD2 84.02 107.9 106 158.5 91.54 106.1 95.4 91.23 60.44 95.64 144.4 214430_at GLA 438.1 375.6 310.1 444.2 406.1 421.4 347.9 353.4 287.7 410.5 327.5 214511_x_at FCGR1B 790 610 504.4 1261 518.3 1320 773.4 399.2 1507 1134 655.9 214629_x_at RTN4 6019 6030 5792 5907 5320 6860 6252 5531 5358 6719 5458 214683_s_at CLK1 4049 3925 3908 3787 3874 4188 4046 3858 3686 3640 3441 214820_at BRWD1 147 109 94.84 116.5 109.6 100.1 75.26 106.6 124.8 90.57 126.4 214853_s_at SHC1 394.1 387.2 421.9 391.3 359.6 369.5 405 315.5 364.7 371.5 412 214931_s_at SRPK2 423.3 383.6 399.1 422.4 459.7 578.8 370.5 490.7 427.8 382.8 369.4 214953_s_at APP 150.8 157.9 191.3 138.4 203.2 142.3 121.5 119.1 116.9 139.8 119.5 215009_s_at SEC31A 680.6 490.5 666.7 583.5 615.3 647.5 414.5 469.2 450 460.9 613.8 215049_x_at CD163 538.4 492 581.8 418.7 368.9 223.6 284.5 260.4 372.1 370.6 236 215273_s_at TADA3L 511.8 425.9 478.1 573.4 489.9 616.9 466.9 502.7 534.3 544.7 572.4 215293_s_at FRAG1 69.95 62.4 76.72 99.83 67.17 83.46 57.94 65.62 66.88 72.27 91.39 215567_at FCF1 141.4 133.5 98.64 132.8 161.1 142.8 151 119.2 118.7 137.9 159.5 215997_s_at CUL4B 444.6 351.2 334 401.9 489.1 447.3 375.1 505 451.5 368.7 379.8 216484_x_at HDGF 394 397.9 419.1 408.6 389.8 356.8 399.7 383 373.8 350.1 343.9 216950_s_at FCGR1A 463.2 282.1 199 585.2 292.1 750.9 384.7 238.9 853 604.5 307.1 217383_at PGK1 30.49 26.89 23.64 29.18 25.71 33.25 26.58 15.09 27.02 30.4 36.64 217403_s_at ZNF227 104.8 97.18 101.1 108.1 87.27 116.2 94.07 84.75 115.1 79.58 144.4 217466_x_at LOC400963///LOC440589 3422 2557 3342 2963 3378 2801 2691 2510 3224 2876 3727 ///LOC441013 ///LOC645173///LOC646294 ///LOC650901 ///LOC729274/// RPS2 217769_s_at POMP 1380 1216 1231 1266 1130 1479 1352 1191 1378 1352 1221 217778_at SLC39A1 225.7 225.2 169.1 192 224.2 234.8 281.5 205.9 200 251.8 196.5 217824_at UBE2J1 296.9 248.8 265.8 267.3 304.6 341.7 297.8 210.3 264.3 313.9 299.4 217987_at ASNSD1 634.6 746.5 652.2 600.8 590.2 893.7 791.4 689.7 745.1 743.7 459.6 217995_at SQRDL 972.1 1287 1463 1504 1499 1530 1523 1460 1651 1584 1196 218012_at TSPYL2 203.7 205.9 253.5 243.2 273.2 211.3 252.7 255 212.2 266.2 293 218040_at PRPF38B 362.6 334.8 388.6 388.9 392.4 402.8 384.1 347.4 358.5 329.4 403.2 218065_s_at TMEM9B 1055 871 1016 1033 932.3 1047 834.4 793.9 964.5 859 1060 218091_at HRB 485.5 464.2 467.1 486 415 490.3 415.8 404.6 372.3 476.5 450.4 218125_s_at CCDC25 61.3 52.67 63.51 60.03 58.7 63.04 56 57.09 58.27 57.9 76.26 218127_at NFYB 248.5 227.4 317 253.8 251 286.3 230.3 236.7 258.5 215.4 284.8 218143_s_at SCAMP2 583.8 589.6 425.4 540.2 469 480.5 672.9 608.1 440.6 549.1 583.8 218206_x_at SCAND1 364.4 333 344 391.6 357.1 354.6 346.1 324.3 365 382.4 373.1 218289_s_at UBE1DC1 101.6 85.64 124 90.82 105.3 110.5 78.08 74.32 114.2 87.56 137.7 218325_s_at DIDO1 331.7 351.2 500 377.7 339.1 327.9 358.1 297.8 349.7 331.6 422.2 218351_at COMMD8 1127 909.3 900.2 1198 1013 1086 857.4 841.5 925 984.4 941.8 218499_at RP6-213H19.1 2573 2350 2469 2538 2607 2482 2229 2576 2207 2236 2594 218627_at DRAM 317.5 326.8 236.3 237.9 349.2 306.5 304.1 372.3 272.4 351.2 244.3 218718_at PDGFC 162.9 108.7 81.93 165.6 77.12 163.9 67.68 47.73 63.04 118.5 83.46 218732_at PTRH2 255.2 210.6 180.5 234.9 253.8 203.2 176.6 136.6 192 193.1 190.1 218845_at DUSP22 911.1 884.8 878.7 837.4 921.2 937.4 760.9 691.4 794.9 763 811.9 218962_s_at TMEM168 458.6 515.8 465 544.7 455.2 564.9 427.5 452.4 403.1 402.6 605.9 219130_at CCDC76 325.7 275.9 335.4 298.3 320.3 264.4 229.3 227.3 278.6 223.8 391.6 219316_s_at FLVCR2 85.94 69.55 67.89 113.6 93.45 102.5 61.74 66.2 69.57 100.7 57.74 219343_at CDC37L1 191.8 154.2 223.8 188.8 211.3 216 175 173.9 146.2 157 221.3 219358_s_at CENTA2 246 139.2 129.7 262.6 204 175.2 114 125.2 155.9 201 122.5 219418_at NHEJ1 136.4 112.4 103.8 100 103.4 79.97 81.83 73.26 85.5 83.11 90.45 219507_at RSRC1 96.34 73.13 88.03 74.42 53.82 100.9 61.91 55.97 56.88 57.62 93.19 219765_at ZNF329 64.2 72.07 76.17 66.86 55.69 80.62 75.7 40.2 67.11 67.48 92.77 219787_s_at ECT2 54.16 43.31 60.18 32.61 82.19 48.07 46.28 43.31 49.34 39.4 43.7 219822_at MTRF1 171.6 198.5 157.5 164.1 147.1 156.9 130.3 149.6 162.7 142.4 205.5 219826_at ZNF419 57.06 42.39 63.96 54.62 39.05 56.72 70.71 32.35 40.19 41.98 81.35 219952_s_at MCOLN1 244.3 137.9 137.9 266.1 203 143.1 214.1 163.7 172.9 158.7 135.2 220044_x_at CROP 5172 4395 5111 4640 5239 5434 3691 3887 4419 4198 5548 220146_at TLR7 136.4 84.15 67.17 164.8 107.1 103.9 55.87 60.3 175.4 93.48 133.8 220160_s_at KPTN 60.51 54.64 47.12 63.3 62.4 55.38 60.5 55.83 73.87 51.87 49.54 220386_s_at EML4 617 405 654.3 652.9 560.6 692.9 499.3 581.7 544.4 552.5 592.5 220578_at ADAMTSL4 66.54 103.4 59.72 102.1 65.22 74.23 77.09 65.03 58.51 69.57 67.33 220605_s_at SIRT2 157.5 160.2 161.3 139.3 159.9 144.6 151.8 149.4 159.5 140.9 155.7 220610_s_at LRRFIP2 122.7 105.9 105 100.9 113.3 100.2 115 101.7 122.8 104 97.27 220690_s_at DHRS7B 135.1 94.8 105.5 122.5 121.9 119.6 103.2 109.7 107.9 121.4 99.34 220750_s_at LEPRE1 98.29 83.23 88.67 92.57 88.63 77.13 91.81 58.98 71.02 69.88 93.23 220865_s_at PDSS1 62.44 85.1 79.22 91.05 111.8 83.33 49.16 54.02 52.8 76.41 81.66 220974_x_at SFXN3 237.4 160.7 187 159.3 112.9 181.2 154 138.9 180.5 156.1 235.2 221011_s_at LBH 782.6 733.2 1236 724.8 721 926.1 893 730.7 983.3 588.6 1467 221206_at PMS2 176.1 173 216.3 159.3 205.8 250.6 191.6 183.9 149.2 154.1 225.4 221264_s_at TARDBP 466.3 517.8 643.2 423.2 400.4 566.2 567 438.6 329.3 395 808.9 221428_s_at TBL1XR1 1286 705.3 797 1133 1047 1111 795.3 1185 846.5 843.8 1093 221449_s_at ITFG1 341.6 286.2 322.8 329.4 367 367.5 287.5 263.8 313 274.3 307.6 221580_s_at JOSD3 1284 1053 1203 1194 1152 1227 1115 1082 1075 931.3 1451 221601_s_at FAIM3 2051 2546 2840 1807 2379 2138 2252 1896 2007 1349 3919 221647_s_at RIC8A 405.7 420.8 504.6 432.9 465.6 438.3 523 445.1 394.7 388.3 431.6 221731_x_at VCAN 7619 5298 6657 7532 6051 5604 5286 5537 6076 7352 4400 221757_at PIK3IP1 559.1 527.5 519.6 484.5 479.4 397.2 522.8 420.9 396.1 534.4 803.7 221841_s_at KLF4 1649 720.6 857.9 1885 1151 1194 681 433 894.7 783.7 830.2 221868_at PAIP2B 39.09 30.5 56.1 31.81 41.04 53 32.47 45.34 34.53 32.52 69.28 221960_s_at RAB2A 61.14 59.15 47.9 53.23 36.75 59.55 57.1 34.68 33.08 40.13 78.62 222217_s_at SLC27A3 290 310.1 228.1 357.6 247.7 198.6 259.9 238.1 340.7 303.2 212 222231_s_at LRRC59 277 268.1 277.1 317.4 250.7 297.5 290.6 233.6 283.4 247.7 268.9 222574_s_at DHX40 895.6 540.7 583.9 513 594.8 568.7 583.4 573.7 470.5 535 539.8 222605_at RCOR3 572 672.9 858.4 739.5 843.8 823.5 750.4 786.9 762.1 746.8 836.2 222651_s_at TRPS1 291.3 244.8 229.3 306.9 326 287.3 205.4 231.1 296.3 270.8 257.5 222670_s_at MAFB 1042 453.6 431.2 969.3 601.3 735.9 342.4 391.3 790 681.3 400 222688_at PHCA 356.5 257.4 171 364 272.9 275.7 257.4 163.7 215.7 252.9 212.2 222700_at ARL6IP2 630.5 627.3 616.8 592.3 503.3 587.9 610.5 496.8 518.5 595.2 543.1 222753_s_at SPCS3 259.9 195.3 180.8 153.6 180.8 185.5 214 151.1 155.3 166.9 182.2 222757_s_at ZAK 88.25 88.83 56.55 85.28 98.7 117.8 83.97 100.5 70.12 89.32 78.88 222774_s_at NETO2 49.53 37.73 41.43 52.28 56.08 38.05 25.12 27.81 43.46 35.23 31.52 222884_at ZNF346 96.89 125 112.7 109.6 116.2 113.6 113.9 119 119.4 88.18 121.2 222980_at RAB10 2207 2120 2614 2333 2120 2327 2139 1916 2361 2530 2100 222982_x_at SLC38A2 3456 4107 3801 3829 4128 3960 3881 3427 3667 4122 3419 223023_at BET1L 275.7 270.5 372.5 282.9 316.2 312.8 283.1 237.4 267.1 280.3 431.9 223064_at RNF181 1324 1267 1180 1274 1387 1352 1252 1323 1309 1238 1252 223158_s_at NEK6 129.7 129.8 88.91 120.2 110.7 90.5 94.32 104.7 83.9 84.28 100.4 223380_s_at LATS2 319 454.2 246.2 265 304.1 300.6 371.7 298 225.9 228.8 282.5 223444_at SENP7 965.7 866.3 769.5 980.4 813.5 785.5 805.1 855.8 918.4 909.8 932.8 223465_at COL4A3BP 374 434.1 305 328.6 497.4 475.3 428.7 383.3 351.3 480 407.3 223590_at ZNF700 434.8 418.6 524.4 403.6 472.8 490.1 406.5 440.9 419.6 432.5 508.7 223686_at TPK1 240.7 228.5 270.9 280.3 210.4 258.5 196.2 212.1 243.5 188 207.8 223801_s_at APOL4 28.34 30.98 33.76 28.73 28.47 23 30.91 30.75 31.46 31.7 29.66 223922_x_at MS4A6A 2483 1898 2172 1795 1419 1529 1241 1296 1994 1723 1394 223982_s_at PNPLA8 1275 1141 987.5 1088 1274 1209 1104 1088 1181 1270 1127 224046_s_at PDE7A 481.4 393.5 478.5 408.5 395.7 438.2 505 469.1 392.4 380.5 639.6 224374_s_at EMILIN2 521.9 399.2 309.7 575.4 520.1 339.9 337.2 393.2 422.9 444.3 363.8 224387_at COMMD5 68.06 63.51 52.34 58.93 70.7 79.41 36.65 56.08 70.16 63.91 57.25 224439_x_at RNF7 458 397.9 425.7 447.6 400.7 403.3 323.2 360.7 384.2 325.5 435.6 224518_s_at ZNF559 344.8 289.5 316.6 288.9 282.2 274.6 250.1 252 262.3 280.1 366 224582_s_at NUCKS1 457.4 278.8 414.1 295.8 350 393.3 276.2 294.8 414 282.1 468.5 224591_at HP1BP3 3243 2622 2970 2992 3023 3290 3037 2957 2745 2409 3575 224726_at MIB1 165.5 187.2 141.2 139.3 167.1 179.6 167.4 120.4 132 143.4 164.3 224818_at SORT1 674.8 668 600.6 777.4 664.4 761.2 514.6 467.9 557.3 579.7 409.8 224917_at MIRN21 2803 2334 2017 2197 2412 2000 1992 2267 2363 2186 1589 224918_x_at MGST1 433.6 287.7 332.5 438.7 436.8 395.6 354.3 340.2 354.1 528.5 255.7 224928_at SETD7 342.8 214.3 273.6 272.4 267.8 247.8 234.1 158.7 206.1 219.9 222.6 225059_at AGTRAP 1123 1313 972.9 1394 1388 1338 1266 1476 1326 1303 1163 225064_at RABEP1 620.9 424.7 384.8 377 411.9 486.7 344.2 422.4 535.1 331.5 579.9 225107_at HNRNPA2B1 2886 2848 3034 3141 3219 2915 2498 2681 2486 2621 3496 225188_at RAPH1 105.1 18.44 27.4 76.44 64.67 45.43 27.58 11.43 21.79 35.14 48.33 225341_at MTERFD3 54.48 81.45 85.53 43.02 51.78 108.5 63.3 47.06 50.93 50.35 83.2 225358_at DNAJC19 95.12 95.28 110.6 98.23 94.91 112.6 94.91 95.75 89.65 71.93 110.5 225365_at ZDHHC20 2733 1965 2188 1992 2466 2068 1828 1899 2471 2170 2224 225388_at TSPAN5 48.73 43.34 51.14 43.42 35.66 74.82 43.83 46.89 56.1 42.15 62.33 225456_at MED1 376 360.9 346.7 400 384.3 466.7 336.6 312.1 349.5 300.9 323.3 225763_at RCSD1 3352 3000 3113 3412 3983 2947 3035 3632 3066 2888 2706 225844_at POLE4 257.4 150.4 179.3 247.7 206.1 183.4 162.1 175.6 205.3 193.4 194.1 225866_at BXDC1 116.7 101.4 98.74 114.9 96.26 121.1 95.9 72.09 98.21 99.56 181 225870_s_at TRAPPC5 732 544.9 517.9 768 712.3 561.4 660.2 563.9 556.1 670.3 497.1 226000_at CTTNBP2NL 26.87 32.79 26.33 27.09 25.79 29.88 18.51 28.97 25.28 25.82 27.05 226030_at ACADSB 122.1 84.28 142.3 117.7 124.1 136.6 102.8 81.34 103.6 101 167.3 226042_at EDC3 98.95 86.31 111.7 92.28 103.6 88.9 106.5 104.2 82.24 94.11 115.5 226059_at TOMM40L 62.29 37.44 31.83 47.25 37.02 60.25 41.37 38.69 43.74 39.55 51.22 226115_at AHCTF1 275.3 325.3 327.1 339 428 402.3 354.4 340.1 289.4 323 334.6 226127_at ALKBH3 85.03 86.41 85.97 87.35 85.33 87.01 86.18 72.58 73.01 78.29 108.9 226218_at IL7R 5517 4898 6481 5330 5313 6331 5144 4197 3977 3268 8914 226220_at METTL9 94.24 88.34 66.87 89.26 83.38 93.08 74.95 86.18 74.48 86.13 126.7 226323_at CCDC16 557.7 539.1 746.7 607.4 607.8 705 526.7 538.5 558.9 582.6 636.6 226353_at SPPL2A 971.4 941.7 852.7 929.9 1083 1068 945.6 937.8 1030 1007 881.1 226428_at TNPO2 186.4 211.5 227 198.4 161 175.1 194.3 184.6 198.3 203.4 213.8 226459_at PIK3AP1 2001 2212 2000 2322 2080 2294 2174 1936 2643 1985 1591 226503_at RIF1 301.5 276.5 229.1 278.3 238.6 232.5 215.6 221.4 286.6 220.3 318.6 226683_at SNAG1 3137 2737 2187 3258 3523 3150 3199 3272 2815 3447 2880 226718_at AMIGO1 85.99 87.32 102 94.15 74.93 77.97 81.11 59.8 66.54 71.42 97.33 226763_at SESTD1 222.7 171 104.5 189.2 132.7 193.3 115.2 110.5 169.6 121 137.5 226836_at SFT2D1 29.71 35.53 37.97 35.4 32.02 34.26 33.08 35.42 37.29 38.31 33.85 227020_at YPEL2 895.4 817.4 794.1 749.3 807.8 835.1 677.4 488.4 664.9 697.3 661.2 227114_at RNF214 107.2 93.54 136.8 120.9 121 100.9 104.8 82.64 83.67 75.33 122.2 227149_at TNRC6C 107.6 72.63 117.2 80.92 73.87 85.91 79.24 74.96 74.98 60.08 113.8 227173_s_at BACH2 108.1 164.2 159.8 110.5 160.7 118.5 153.7 87.84 145.2 108.9 229.3 227213_at ADAT2 89.18 66.52 77.56 78.34 71.4 122.7 65.72 54.35 70.36 61.75 116.8 227374_at EARS2 57.91 59.08 56.32 46.97 52.93 56.03 40.39 46.67 63.07 51.61 58.18 227517_s_at GAS5 634.8 507.9 703.6 478.6 478.3 491 437.4 380.9 494.8 368.4 851.8 227558_at CBX4 1383 1294 1334 1227 1477 1499 1269 1527 1285 1295 1487 227560_at SFXN2 116 76.77 103 100.3 92.3 103.9 92.1 78.79 110.7 101.1 112.9 227722_at RPS23 360.2 216.9 185.8 153.9 43.85 160.7 250.3 154.8 103.4 176.4 499.5 227990_at SLU7 1175 988.9 1142 1099 1152 1066 982.9 1077 973.1 1221 1059 228012_at MATR3 28.96 23.94 36.07 27.77 27.74 33.4 23.94 24.63 33.37 27.71 46 228170_at OLIG1 422.6 417 405.3 628.9 751.4 440.5 441.3 217.7 216.4 368.7 239.9 228176_at EDG3 213.8 129 267.8 386.4 280.2 181.1 194.6 116.8 154 235.5 164.9 228234_at TICAM2 378.8 334.8 304.7 453.9 323.3 273.8 301.7 263 331.2 300.3 280.1 228370_at SNRPN 172.7 164.6 178.2 136.2 145.6 209 175.6 147 132.9 136 363.6 228549_at TMEM63A 538.2 551.8 626.4 390.7 476.3 461.8 541.8 441.9 421.9 386.2 769.2 228630_at ZNF84 88.84 83.66 131.1 94.63 104.7 108.9 82.32 118.7 88.18 90.52 154.2 228831_s_at GNG7 156.4 187.9 270.6 141.9 224.4 172.2 206 210 165.1 190.9 343.2 229307_at ANKRD28 41.67 46.67 50.85 16.49 37.52 43.65 18.25 37.9 23.43 57.59 33.36 229421_s_at FLJ20273 33.77 35.13 36.56 38.62 39.14 35.99 39.08 38 35.65 45.92 31.44 229509_at MFSD8 294.7 228.3 189.7 221.4 249.7 189.9 204.7 259.7 245.1 194.3 311.4 229854_at OBSCN 24.53 27.2 25.74 25.36 29.61 25.38 25.24 25.44 26.87 26.25 36.75 229982_at QSER1 104.3 86.7 75.26 53.61 53.1 76.63 72.66 61.15 63.19 74.71 84.23 230265_at SEL1L 137.8 157.7 129.3 123.5 135.9 117.7 114 78.51 109.2 194 123.5 230320_at TBRG1 139.3 128.1 153.1 175.8 169.4 156 120.8 138.8 169.6 113.6 170.6 230408_at PCGF3 101.1 93.69 105.7 103.9 82.8 110.3 104.7 76.24 86.28 79.52 130 230480_at PIWIL4 56.79 45.57 39.91 58.63 60.72 63.07 45.93 41.8 54.47 54.72 49.92 230837_at LOC647500 87.73 74.83 70.88 85.38 81.38 82.84 75.87 111.8 99.75 86.91 81.53 230852_at STAC3 53.88 38.09 40.34 49.17 45.89 35.34 35.12 42.72 42.98 45.13 33.93 230922_x_at FUNDC2 45.32 43.74 47.19 52.73 45.43 52.67 43.7 60.61 53.53 49.78 53.56 231283_at MGAT4A 253.3 269.5 304.1 197.6 200.8 301.3 215.9 203.6 260.2 198.5 288 231697_s_at TMEM49 106.6 77.76 54.63 55.53 50.45 52.01 54.71 58.2 57.59 56.2 70.56 231836_at HKR1 68.13 76.92 135.6 64.18 51.8 50.94 82.85 71.85 75.48 66.03 103.4 231843_at DDX55 246.2 214.1 203.1 217.8 190.5 179.6 216.4 210.4 184.3 158.5 217.6 231845_at AARS2 140.4 114 98.37 142.6 102.1 122.2 105.6 97.6 92.53 105.3 169 231904_at U2AF1 445.6 453.4 384.6 452.1 451.5 332.7 343.5 436.9 329.5 501.8 497.6 231914_at NUDT14 46.57 47.88 49.78 48.73 46.99 42.49 47.74 48.43 49.35 44.66 44.78 232636_at SLITRK4 68.55 57.31 32.95 66.84 76 55.93 41.77 20.75 42.23 67.88 44.46 232851_at FBXO3 58.99 44.27 47.54 52.52 74.7 45.57 52.54 75.3 42.02 70.1 62.22 233019_at CNOT7 404.1 306.5 270.5 352.2 357.3 276.5 316.5 322.8 275.7 309.1 446.5 233169_at ZNF350 117.1 116.4 118.6 136.5 128.7 113.4 105.5 115.1 100 163.7 140 234013_at TRA@ 177 69.59 73.2 121.3 70.36 106.2 83.8 78.28 115.1 78.43 207.9 234311_s_at GTPBP10 152.7 140.2 186.6 158.2 142.8 163.6 107 128.8 179.3 137.8 189.4 234339_s_at GLTSCR2 1991 1592 2345 1935 1569 1855 1400 1226 1612 1808 2952 234464_s_at EME1 26.74 32.8 23.03 25.23 34.62 36.05 23.49 28.07 26.82 33.2 47.56 234733_s_at FANCM 38.56 31.84 30.04 33.16 34.28 29.68 25.69 25.58 29.42 30.84 46.44 235024_at PHF17 111 116.7 121.4 100.8 93.65 95.62 119.8 88.88 95.94 101.1 119.8 235067_at MKLN1 942.6 1156 943 1187 1147 800.8 1137 1074 989.1 1002 877.7 235200_at ZNF561 163 134.8 103.4 145.9 122.6 106.6 109.8 111.3 119 139.7 176 235359_at LRRC33 349 274.1 205.3 354.2 270.6 276.3 259.6 141.7 196.1 202.2 277.7 235593_at ZEB2 774.5 621.8 383.5 691 551.3 697.8 425.5 570.5 673.3 596.4 396.7 235610_at ALKBH8 76.87 65.27 54.86 79.96 64.83 69.17 54.25 52.08 74.79 55.08 124.8 235623_at ELP2 28.21 29.65 31.13 28.68 24.94 28.01 29.69 28.54 28.6 32 34.98 235690_at ZNF594 37.8 23.62 25.94 26.28 29.1 23.87 30.93 23.36 25.26 31.5 47.45 237504_at INTS10 91.75 86.89 65.38 77.54 71.72 74.29 62.18 84.13 86.26 85.47 88.46 238429_at TMEM71 4027 4738 4531 3774 4731 4141 5656 6250 3875 5472 4497 238513_at PRRG4 589.6 949.5 477 1593 1249 756 1482 751.4 1221 402.5 654.9 238736_at REV3L 327.9 339.4 291.1 269.8 259.7 266.8 425 307.4 234.2 272.7 301.6 238823_at FMNL3 61.1 46.66 65.56 58.07 59.27 50.35 50.2 71.76 64.37 55.51 55.84 238909_at S100A10 290.4 144.4 147.8 124 135.2 142.1 147.7 95.89 124.8 107 100.2 239108_at MLSTD1 178.9 252.9 234.4 154.7 269 212.3 223.2 204.8 263.9 250.3 153.4 239897_at BCLAF1 270.6 247.8 268.8 231.5 247.9 215 213.3 223.8 185.1 231.3 239 241368_at LSDP5 208.9 352.2 299.6 367.3 403.6 307 307 386.1 278.3 500.8 310.7 241704_x_at ZNF320 73.27 49.49 37.61 56.8 63.24 60.61 52.28 49.45 54.62 52.44 72.77 241706_at CPNE8 168.5 118.6 98.83 121.4 94.15 119.2 91.99 78.89 91.27 92.01 100.2 241731_x_at ZNF440 67.29 60.8 56.78 58.38 69.95 51.15 56.35 53.25 52.34 52.59 60.91 242197_x_at CD36 47.53 15.07 20.04 55.01 40.17 56.45 35.62 32.33 17.05 50.8 48.93 242561_at IPO9 41.02 33.29 27.38 35.98 24.53 31.99 21.94 24.1 30.9 26.28 25.3 242569_at STAM2 326.4 310.2 241.7 342.1 330.3 300.2 268 335.8 289.4 360.2 313.5 242669_at UFM1 297 278 262.7 302.8 265.1 305 209.4 221.3 324.4 220.8 225.1 243982_at KLHL28 132.6 92.12 103.6 134.6 158.1 95.4 139.1 109 109 103.5 148.4 244038_at WDR89 52.43 50 51.77 61.11 53.37 47.74 57.74 40.12 58.36 42.46 68.6 244654_at MYO1G 1789 1596 1853 1498 1338 1372 1402 1367 1335 1377 1486 244698_at CDRT4 31.83 33.58 42.34 44.12 33.24 33.79 30.11 33.85 38.15 37.21 32.34 36566_at CTNS 114.3 100.2 112.3 119 101.5 95.52 83.74 86.35 77.96 99.66 108.5 37549_g_at BBS9 47.53 37.19 46.39 43.79 42.47 42.57 37.35 43.14 43.51 38.7 43.04 48659_at RP5-1077B9.4 199.5 185.6 172.4 192.4 201.1 169.6 215.8 171 192.1 197.7 219.6 56829_at NIBP 133 170.3 149.8 157.1 150.7 137.2 132.9 170.5 154.9 146.6 150.2 64486_at CORO1B 250.8 188.8 148.6 252.7 279.1 197.1 220 167 172 182.4 213.5 65493_at HEATR6 56.59 35.06 42.69 39.23 34.23 40.4 41.43 33.94 41.52 23.55 37.68 AFFX- GAPDH 8347 7922 8861 8956 8248 7472 8602 8829 7532 9750 8389 HUMGAPDH/M33197_3_at NYHA NYHA NYHA NYHA Control Control Control Control Control Control Control Control Control I-II I-II I-II I-II Affymetrix Probe Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample set ID no. 11 no. 12 no. 13 no. 14 no. 15 no. 16 no. 19 no. 21 no. 29 no. 31 no. 33 no. 34 no. 35 1552318_at 2180 1941 1659 1741 2171 1068 1800 1347 1780 1591 2961 1998 1270 1552630_a_at 80.26 85.67 112.5 80.08 82.08 75.01 138.6 72.66 127.8 80.54 120.7 81.18 94.63 1554149_at 783.8 745.1 840.5 715.5 833.1 608.4 787.4 768.6 884.9 682.5 759.4 723.7 863.8 1554539_a_at 94.56 106.4 88.55 77.94 117.9 57.39 74.83 54.93 83.8 54.31 104.1 116.2 69.98 1554606_at 155.9 128.1 117.4 167.2 172.1 136.6 126.6 156.4 141.7 62.39 173.8 113.9 120.4 1555630_a_at 131.1 101.1 102.8 125.7 157.2 85.99 143.4 100.9 94.46 117.5 87.08 292 90.07 1555963_x_at 29.58 41.06 49.48 40.71 51.69 46.88 46.88 46.88 41.91 53.58 44.09 65.59 60.24 1555996_s_at 1162 1107 796.4 1138 1198 771.6 1194 639.8 980.2 247.1 1391 1217 850.3 1556113_at 29.78 45.44 39.82 29.05 37.23 38.7 40.81 41.72 32.63 49.86 28.92 52.49 34.93 1556283_s_at 130.7 114.9 96.99 117.5 89.51 144 88.41 80.86 107.2 107.2 79.99 124 115.5 1556864_at 61.7 77.04 58.94 46.05 51.03 47.33 56.31 50.05 46.87 46.94 47.15 47.21 31.95 1557066_at 199.7 160.4 153.3 210.7 219.2 123 157 156.1 238.5 112 297.5 198 156.4 1558277_at 27.12 43.58 39.73 25.89 40.88 44.61 27.02 30.47 23.92 34.37 40.74 48.45 35.13 1558755_x_at 196 153 207.2 132.6 159.3 186.8 154.3 228.6 132.2 134.5 146.2 121 80.78 1561146_at 96.38 65.76 65.76 75.08 100.6 155.3 87.59 60.16 86.45 81.61 90.64 72.6 38.85 1564962_at 29.45 50.32 34.43 46.31 30.9 51.92 40.27 30.69 31.47 28.56 36.96 47.11 22.78 1567013_at 106.9 103.3 95.28 135.3 95.36 169 111.8 104.9 91.88 85.32 79.6 72.51 80.6 1568815_a_at 152.6 103.4 159.2 139.7 180 217 153.6 163.8 175.6 198.7 201 224.1 135.5 200007_at 7220 6459 7980 8188 7727 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528.8 496.6 467.6 498.3 200950_at 432.1 473.2 447.4 553.6 491.1 557.6 520.9 516.2 476.3 370.7 475.1 482.1 576 201031_s_at 10377 8079 9773 7760 10535 6495 9850 8607 10650 10046 10812 11153 9596 201075_s_at 340.9 283.4 376.8 292.2 350.2 295.4 384.2 347.9 361.8 264.2 382 298.9 338.5 201098_at 726.6 713.9 821.1 828.5 783.1 788 868.6 755.1 788.6 734.6 791.9 773.7 828.5 201105_at 2461 3190 2515 3836 3588 1856 6006 1566 3805 3895 3013 4701 3644 201172_x_at 2860 3093 3348 3580 3239 3718 3675 3678 3017 3461 2989 3153 3509 201186_at 527.7 381.9 483.4 384.1 369.2 489.3 542 531.3 446.7 612.2 448.3 367.4 588 201193_at 436.6 505.8 523 573.3 468 551 570.9 409.5 392.2 491.8 433.6 468.7 587.5 201198_s_at 145 162.5 145 185.6 156.5 133.4 176.4 139.8 147.3 168.8 164.9 226.7 167.2 201220_x_at 1215 1767 1498 1414 1352 1792 1934 1515 1468 1665 1107 1825 1688 201234_at 1030 1091 1178 1193 1147 989.3 1333 1098 1096 1193 1132 1254 1303 201357_s_at 302.3 354.3 390.9 309.7 434.1 429.1 395.4 361.5 358.7 273.1 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572.4 621.3 713.5 627.8 201031_s_at 7860 9695 8016 7455 7555 5837 6285 5138 201075_s_at 274.1 268.4 323.5 281.9 336.6 322.2 255.4 256.1 201098_at 836.5 737.2 857.4 876.6 942.8 873.5 1037 726.1 201105_at 4353 3468 4549 3442 4419 3858 7914 2989 201172_x_at 3619 3478 3557 3290 3646 4218 3933 4021 201186_at 729.1 703.5 718.7 580.2 594.5 618.6 702.7 620.2 201193_at 643.4 747.9 588.8 676.6 802.2 822.7 894.4 618.2 201198_s_at 173.8 168.1 168.1 171.9 216.2 162.4 163.4 147.1 201220_x_at 1680 1799 1739 1602 1970 2084 1564 2018 201234_at 1341 1314 1562 1578 1126 1431 1414 1093 201357_s_at 331.5 351.2 345 241.2 356.4 418.4 275.5 333.5 201363_s_at 1647 1074 1451 1435 1756 1435 1159 1580 201400_at 1845 1887 2271 1871 1845 2170 2708 2445 201421_s_at 143.3 179.5 136 153.1 168.2 116.7 178.9 151.1 201422_at 8633 8331 10490 9029 8352 9837 10893 7702 201426_s_at 20814 13614 19843 14682 18299 18494 17298 16129 201453_x_at 1390 1328 1297 1263 1405 1326 1463 1385 201470_at 1485 1461 1757 1352 1163 1393 2243 1283 201478_s_at 223.1 213.5 235.5 250 287.7 164.3 237.9 197.4 201527_at 933.9 1170 1000 1003 784.5 1054 1162 807.8 201536_at 535.8 378.5 392.3 424.1 444.2 605.7 544.4 515.2 201554_x_at 1187 678.9 897 823.8 820.9 842.3 1030 1370 201556_s_at 592.5 522.3 496.6 557.5 783.5 497.7 447.6 536.7 201576_s_at 647.7 683.2 799.2 759.1 805.7 834.9 955.8 710.9 201590_x_at 3688 3455 3865 3583 3698 3581 4903 3255 201628_s_at 614.7 631.3 713.4 613.4 629.8 667.6 695.2 657.5 201788_at 501.3 563.9 501.3 520.2 577.6 416.2 482.5 499.6 201900_s_at 460.9 551.5 476.9 518.7 369 485.4 741.4 388.9 201945_at 549.2 598.5 563.2 484.2 661.6 613.8 428.5 618.1 202068_s_at 201.3 160.9 159.7 105.3 130.8 233.1 164.7 78.83 202104_s_at 179.3 373.7 459.3 310.1 338.3 258.6 327.9 242.2 202138_x_at 252.6 320.2 276.9 272 253.1 261.8 340.1 280.1 202185_at 248.2 308.9 211.1 247 217 224.8 240.2 169.5 202192_s_at 918.6 844.3 946.5 640.3 1091 1105 1067 788.3 202201_at 670.1 709.7 780.1 713.1 762.4 889.5 1467 631.8 202249_s_at 204.2 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101 87.42 100.3 89.76 81.67 109.3 94.02 227149_at 73.98 52.82 73.3 59.92 73.53 48.25 59.08 67.2 227173_s_at 69.74 152.6 127.7 62.28 115.6 42.21 51.18 62.72 227213_at 54.67 65.79 53.55 75.97 62.79 31.43 50.33 38.77 227374_at 41.02 49.75 49.13 46.48 43.8 48.35 41.54 32.07 227517_s_at 382.4 495.9 381.8 400.3 424.7 267.3 315.5 244.5 227558_at 1169 1019 1247 1274 1375 1018 1170 1228 227560_at 79.71 85.84 92.04 76.38 77.83 86.21 81.59 77.5 227722_at 39.07 215.9 81.54 59.97 70.18 123.4 62.19 169.9 227990_at 898.6 827.2 993.2 888.8 1033 1041 1081 1144 228012_at 23.21 24.09 30.34 24.26 23.75 22.7 24.79 20.43 228170_at 826.7 814.5 482.8 1380 737.3 374.8 343.8 1017 228176_at 151.2 280.6 267.2 285.9 325 249.8 494.8 245.5 228234_at 363.8 319.6 388 412.5 383.3 410.6 508.4 396.1 228370_at 175.4 203.5 125.4 94.97 172.2 59.9 89.81 97.52 228549_at 393.7 493.8 484.2 359.7 440 334.9 390.5 294.4 228630_at 111.3 98.54 71.13 82.12 109.9 40.19 72.6 67.41 228831_s_at 76.18 163.4 138.1 141.2 182.1 147.1 78.18 129.1 229307_at 144.5 53.17 122.1 48.33 86.89 88.36 30.81 45.07 229421_s_at 63.84 33.5 34.92 41.39 48.57 57.7 44.52 69.42 229509_at 220 176 221.1 211.4 228.2 181 201 225.3 229854_at 23.01 25.66 25.16 22.46 25.24 24.8 24.32 25.71 229982_at 131.9 152.5 113.1 85.15 134.8 92.66 110.6 97.69 230265_at 250.1 144.4 172.4 126.7 249 299.9 180.1 301 230320_at 102 136.1 125.6 119 122.4 113.9 126.5 92.83 230408_at 79.05 102.9 88.83 88.67 83.7 79.85 93.17 77.97 230480_at 73.89 73.2 74.35 58.36 67.04 58.25 66.48 59.78 230837_at 59.38 62.6 72.9 65.66 81.91 64.09 58.46 69.66 230852_at 48.85 47.9 46.24 46.28 41.68 52.01 46.24 50.42 230922_x_at 43.79 39.91 34.58 48.67 42.8 44.91 41.58 38.7 231283_at 173.9 143.8 140.2 194 254.5 188.8 145.2 122.2 231697_s_at 115.4 90.57 88.37 75.7 98.91 67.16 136.8 96.89 231836_at 50.38 72.41 62.82 49.21 54.65 44.4 50.75 38.98 231843_at 152.9 197.8 168.6 164 171.6 117.2 134.2 119.9 231845_at 84.15 156.8 87.16 85.64 95.25 72.56 89.09 82.37 231904_at 248.8 381.3 376.9 298.7 346.7 361.7 284.8 383.9 231914_at 50.22 59.14 49.9 47.38 42.32 48.65 72.57 59.32 232636_at 105.9 68.64 93.72 83.66 115.9 69.18 111.3 64.25 232851_at 42.05 39.62 37.81 37.2 52.68 45.35 29.08 45.9 233019_at 209 275.8 296.1 286.9 299 178.5 257.1 182.4 233169_at 72.93 87.16 87.44 76.06 87.85 87.61 96.7 110.3 234013_at 123 81.02 56.57 106.2 62.31 66.35 119.7 61.44 234311_s_at 97.92 135.3 109.7 111.1 151.4 144 109.5 153 234339_s_at 1379 2451 1009 1131 1627 1209 1925 875.9 234464_s_at 49.51 52.24 36.24 52.35 47.78 26.37 33.89 38.03 234733_s_at 21.67 23.31 27.12 27.16 41.12 21.89 31.66 29.26 235024_at 94.65 90.02 88.97 79.49 94.07 94.46 101 83.25 235067_at 770.7 886 1043 1025 806.5 929.2 791.6 955.5 235200_at 78.26 156.4 119.7 105.7 95.74 105.1 118.6 89.77 235359_at 280.1 417.6 361 384.8 339.1 287.7 432.1 334.3 235593_at 1198 651.4 913 654.9 1161 911.6 683.5 1015 235610_at 50.59 55.12 41.23 58.57 64.9 39.29 56.86 46.59 235623_at 26.12 28.6 26.79 25.21 24.53 20.77 22.07 18.78 235690_at 25.46 24.71 25.92 22.28 21.76 22.9 19.01 16.87 237504_at 55.55 84.3 61.51 55.96 66.37 76.06 74.67 76.21 238429_at 2653 2933 3541 3913 3214 4244 4476 5591 238513_at 1606 873.2 928.8 1326 1558 1900 1081 1048 238736_at 297.6 272.2 262.6 210.8 228.1 205.5 244.9 216 238823_at 45.69 53.25 40.79 37.02 33.74 32.49 24.83 34.4 238909_at 389.9 170.7 261.4 213.2 225.3 167.8 325.7 148.8 239108_at 346 274.4 316.8 281.6 365.5 521.1 332.9 283.5 239897_at 223.8 169.2 210 184.6 229.7 264.1 193.9 263.9 241368_at 430.8 319.1 436.6 335.2 300 447 295.1 568.2 241704_x_at 45.76 69.14 50 52.36 32.26 43.66 38.3 44.75 241706_at 128 123.7 131.8 117.3 151 159.3 197.5 130.2 241731_x_at 46.56 47.55 56.84 44.62 56.51 50.21 46.91 47.59 242197_x_at 56.68 112.7 128.9 66.44 145.5 88.9 79.35 81.35 242561_at 24.62 24 15.43 23.47 26.56 23.23 22.78 25.29 242569_at 194.8 190 254.7 283.4 269.1 273.4 259.7 338.8 242669_at 206.4 290.1 232.3 241.3 327.7 182.2 234 179.2 243982_at 95.87 76.44 99.57 97.14 114.7 97 80.27 77.12 244038_at 41.11 44.97 35.9 38.62 48.81 40.07 39.69 27.91 244654_at 1532 2423 2975 2086 1421 1916 1808 1378 244698_at 33.16 34.56 33.28 30.61 29.97 30.63 33.55 34.85 36566_at 118.6 127.3 130.1 157.1 124 135.4 152.4 98.89 37549_g_at 42.75 44.25 40.07 46.18 42.52 43.78 42.79 46.12 48659_at 256.1 271.2 249 207.9 181.3 242.7 234.3 185.7 56829_at 140.2 171.7 166.2 149.9 133.2 216 163.5 160.8 64486_at 259.5 306.1 249.3 243.2 253.2 316.2 380.4 172.1 65493_at 55.4 39.22 46.3 40.81 45.25 37.45 49.23 40.56 AFFX- 11426 10898 11477 11311 8295 11212 11537 9700 HUMGAPDH/M33197_3_at

TABLE 2 Affymetrix GenBank Probe set ID Gene symbol Accession No. Gene Title 1552318_at GIMAP1 AK091818 GTPase, IMAP family member 1 1552630_a_at SRCAP NM_006662 Snf2-related CBP activator protein 1554149_at CLDND1 BC013610 claudin domain containing 1 1554539_a_at RHOF BC018208 ras homolog gene family, member F (in filopodia) 1554606_at CCDC100 BC040527 coiled-coil domain containing 100 1555630_a_at RAB34 AF327350 RAB34, member RAS oncoqene family 1555963_x_at B3GNT7 CA503291 UDP-GlcNAc:betaGal beta-1,3-N- acetylglucosaminyltransferase 7 1555996_s_at EIF4A2 A1332397 eukaryotic translation initiation factor 4A, isoform 2 1556113_at DKFZp451A211 BC036906 DKFZp451A211 protein 1556283_s_at FGFR1OP2 W74643 FGFR1 oncoqene partner 2 1556864_at TECT1 BC030993 tectonic 1 1557066_at LUC7L AI744735 LUC7-like (S. cerevisiae) 1558277_at ZNF740 BM786513 zinc finger protein 740 1558755_x_at ZNF763 AA484731 zinc finger protein 763 1561146_at VPS35 N51700 vacuolar protein sorting 35 homolog (S. cerevisiae) 1564962_at ZNF92 M61872 zinc finger protein 92 1567013_at NFE2L2 AF323119 nuclear factor (erythroid-derived 2)-like 2 1568815_a_at DDX50 AA903184 DEAD (Asp-Glu-Ala-Asp) box polypeptide 50 200007_at SRP14 NM_003134 signal recognition particle 14 kDa (homologous Alu RNA binding protein) 200010_at RPL11 NM_000975 ribosomal protein L11 200059_s_at RHOA BC001360 ras homoloq gene family, member A 200091_s_at RPS25 AA888388 ribosomal protein S25 200633_at UBB NM_018955 ubiquitin B 200650_s_at LDHA NM_005566 lactate dehydroqenase A 200672_x_at SPTBN1 NM_003128 spectrin, beta, non-erythrocytic 1 200677_at PTTG1IP NM_004339 pituitary tum or-transforming 1 interacting protein 200713_s_at MAPRE1 NM_012325 microtubule-associated protein, RP/EB family, member 1 200822_x_at TPI1 NM_000365 triosephosphate isomerase 1 200829_x_at ZNF207 NM_003457 zinc finger protein 207 200839_s_at CTSB NM_001908 cathepsin B 200932_s_at DCTN2 NM_006400 dynactin 2 (p50) 200950_at ARPC1A NM_006409 actin related protein 2/3 complex, subunit 1A, 41 kDa 201031_s_at HNRPH1 NM_005520 heterogeneous nuclear ribonucleoprotein H1 (H) 201075_s_at SMARCC1 NM_ 003074 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily c, member 1 201098_at COPB2 NM_004766 coatomer protein complex, subunit beta 2 (beta prime) 201105_at LGALS1 NM_002305 lectin, galactoside-binding, soluble, 1 (galectin 1) 201172_x_at ATP6V0EI NM_003945 ATPase, H+ transporting, lysosomal 9 kDa, V0 subunit e1 20 186_at LRPAP1 NM_002337 low density lipoprotein receptor-related protein associated protein 1 201193_at IDH1 NM_005896 isocitrate dehydrogenase 1 (NADP+), soluble 201198_s_at PSMD1 AI860431 proteasome (prosome, macropain) 26S subunit, non-ATPase, 1 201220_x_at CTBP2 NM_001329 C-terminal binding protein 2 201234_at ILK NM_004517 integrin-linked kinase 201357_s_at SF3A1 NM_005877 splicing factor 3a, subunit 1, 120 kDa 201363_s_at IVNS1ABP AB020657 influenza virus NS1A binding protein 201400_at PSMB3 NM_002795 proteasome (prosome, macropain) subunit, beta type, 3 201421_s_at WDR77 NM_024102 WD repeat domain 77 201422_at IFI30 NM_006332 interferon, gamma-inducible protein 30 201426_s_at VIM AI922599 vimentin 201453_x_at RHEB NM_005614 Ras homolog enriched in brain 201470_at GSTO1 NM_004832 glutathione S-transferase omega 1 201478_s_at DKC1 U59151 dyskeratosis congenita 1, dyskerin 201527_at ATP6V1F NM_004231 ATPase, H+ transporting, lysosomal 14 kDa, V1 subunit F 201536_at DUSP3 AL048503 dual specificity phosphatase 3 (vaccinia virus phosphatase VH1-related) 201554_x_at GYG1 NM_004130 glycogenin 1 201556_s_at VAMP2 BC002737 vesicle-associated membrane protein 2 (synaptobrevin 2) 201576_s_at GLB1 NM_000404 galactosidase, beta 1 201590_x_at ANXA2 NM_004039 annexin A2 201628_s_at RRAGA NM_006570 Ras-related GTP binding A 201788_at DDX42 NM_007372 DEAD (Asp-Glu-Ala-Asp) box polypeptide 42 201900_s_at AKR1A1 NM_006066 aldo-keto reductase family 1, member A1 (aldehyde reductase) 201945_at FURIN NM_002569 furin (paired basic amino acid cleaving enzyme) 202068_s_at LDLR NM_000527 low density lipoprotein receptor (familial hypercholesterolemia) 202104_s_at SPG7 NM_003119 spastic paraplegia 7 (pure and complicated autosomal recessive) 202138_x_at JTV1 NM_006303 JTV1 gene 202185_at PLOD3 NM_001084 procollagen-lysine, 2-oxoglutarate 5- dioxygenase 3 202192_s_at GAS7 NM_005890 growth arrest-specific 7 202201_at BLVRB NM_000713 biliverdin reductase B (flavin reductase (NADPH)) 202249_s_at WDR42A AU146233 WD repeat domain 42A 202252_at RAB13 NM_002870 RAB13, member RAS oncogene family 202262_x_at DDAH2 NM_013974 dimethylarginine dimethylaminohydrolase 2 202380_s_at NKTR NM_005385 natural killer-tumor recognition sequence 202381_at ADAM9 NM_003816 ADAM metallopeptidase domain 9 (meltrin gamma) 202428_x_at DBI NM_020548 diazepam binding inhibitor (GABA receptor modulator, acyl-Coenzyme A binding protein) 202445_s_at NOTCH2 NM_024408 Notch homolog 2 (Drosophila) 202461_at E F2B2 NM_ 014239 eukaryotic translation initiation factor 2B, subunit 2 beta, 39 kDa 202522_at PITPNB AL031591 phosphatidylinositol transfer protein, beta 202523_s_at SPOCK2 AI952009 sparc/osteonectin, cwcv and kazal-like domains proteoglycan (testican) 2 202594_at LEPROTL1 NM_015344 leptin receptor overlapping transcript-like 1 202623_at EAPP NM_018453 E2F-associated phosphoprotein 202652_at APBBI NM_001164 amyloid beta (A4) precursor protein-binding, family B, member 1 (Fe65) 202724_s_at FOXO1 NM_002015 forkhead box O1 202750_s_at TFIP11 AL080147 tuftelin interacting protein 11 202778_s_at ZMYM2 NM_003453 zinc finger, MYM-type 2 202910_s_at CD97 NM_001784 CD97 molecule 202928_s_at PHF1 NM_024165 PHD finger protein 1 202944_at NAGA NM_000262 N-acetylgalactosaminidase, alpha- 202979_s_at CREBZF NM_021212 CREB/ATF bZIP transcription factor 203003_at MEF2D AL530331 myocyte enhancer factor 2D 203127_s_at SPTLC2 BC005123 serine palmitoyltransferase, long chain base subunit 2 203137_at WTAP NM_004906 Wilms tumor 1 associated protein 203184_at FBN2 NM_001999 fibrillin 2 (congenital contractural arachnodactyly) 203234_at UPP1 NM_003364 uridine phosphorylase 1 203278_s_at PHF21A NM_016621 PHD finger protein 21A 203305_at F13A1 NM_000129 coagulation factor XIII, A1 polypeptide 203371_s_at NDUFB3 NM_002491 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 3, 12 kDa 203413_at NELL2 NM_006159 NEL-like 2 (chicken) 203416_at CD53 NM_000560 CD53 molecule 203492_x_at CEP57 AA918224 centrosomal protein 57 kDa 203534_at LSM1 NM_014462 LSM1 homolog, U6 small nuclear RNA associated (S. cerevisiae) 203535_at S100A9 NM_002965 S100 calcium binding protein A9 203578_s_at SLC7A6 BG230586 solute carrier family 7 (cationic amino acid transporter, y+ system), member 6 203748_x_at RBMS1 NM_016839 RNA binding motif, single stranded interacting protein 1 203759_at ST3GAL4 NM_006278 ST3 beta-galactoside alpha-2,3-sialyltransferase 4 203844_at VHL NM_000551 von Hippel-Lindau tumor suppressor 203880_at COX17 NM_005694 COX17 cytochrome c oxidase assembly homoloq (S. cerevisiae) 203912_s_at DNASE1L1 NM_006730 deoxyribonuclease I-like 1 203939_at NT5E NM_002526 5′-nucleotidase, ecto (CD73) 203971_at SLC31A1 NM_001859 solute carrier family 31 (copper transporters), member 1 204050_s_at CLTA NM_001833 clathrin, light chain (Lca) 204068_at STK3 NM_006281 serine/threonine kinase 3 (STE20 homolog, Yeast) 204099_at SMARCD3 NM_003078 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily d, member 3 204143_s_at ENOSF1 NM_017512 enolase superfamily member 1 204204_at SLC31A2 NM_001860 solute carrier family 31 (copper transporters), member 2 204214_s_at RAB32 NM_006834 RAB32, member RAS oncogene family 204232_at FCER1G NM_004106 Fc fragment of IgE, high affinity I, receptor for; gamma polypeptide 204243_at RLF NM_012421 rearranged L-myc fusion 204249_s_at LMO2 NM_005574 LIM domain only 2 (rhombotin-like 1) 204291_at ZNF518 NM_014803 zinc finger protein 518 204342_at SLC25A24 NM_013386 solute carrier family 25 (mitochondrial carrier; phosphate carrier), member 24 204352_at TRAF5 NM_004619 TNF receptor-associated factor 5 204401_at KCNN4 NM_002250 potassium intermediate/small conductance calcium-activated channel, subfamily N, member 4 204504_s_at HIRIP3 NM_003609 HIRA interacting protein 3 204617_s_at ACD NM_022914 adrenocortical dysplasia hornolog (mouse) 204645_at CCNT2 NM_001241 cyclin T2 204675_at SRD5A1 NM_001047 steroid-5-alpha-reductase, alpha polypeptide 1 (3-oxo-5 alpha-steroid delta 4-dehydrogenase alpha 1) 204689_at HHEX NM_001529 hematopoietically expressed homeobox 204801_s_at DHRS12 NM_024705 dehydrogenase/reductase (SDR family) member 12 205235_s_at MPHOSPH1 NM_016195 M-phase phosphoprotein 1 205254_x_at TCF7 AW027359 transcription factor 7 (T-cell specific, HMG-box) 205256_at ZBTB39 NM_014830 zinc finger and BTB domain containing 39 205322_s_at MTF1 AW182367 metal-regulatory transcription factor 1 205340_at ZBTB24 NM_014797 zinc finger and BTB domain containing 24 205349_at GNA15 NM_002068 guanine nucleotide binding protein (G protein), alpha 15 (Gq class) 205550_s_at BRE NM_004899 brain and reproductive organ-expressed (TNFRSF1A modulator) 205811_at POLG2 NM_007215 polymerase (DNA directed), gamma 2, accessory subunit 205835_s_at YTHDC2 AW975818 YTH domain containing 2 205895_s_at NOLC1 NM_004741 nucleolar and coiled-body phosphoprotein 1 205965_at BATF NM_006399 basic leucine zipper transcription factor, ATF-like 205976_at FASTKD2 NM_014929 FAST kinase domains 2 206015_s_at FOXJ3 NM_014947 forkhead box J3 206037_at CCBL1 NM_004059 cysteine conjugate-beta lyase; cytoplasmic (glutamine transaminase K, kyneurenine aminotransferase) 206170_at ADRB2 NM_000024 adrenergic, beta-2-, receptor, surface 206182_at ZNF134 NM_003435 zinc finger protein 134 206343_s_at NRG1 NM_013959 neuregulin 1 206542_s_at SMARCA2 AV725365 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 2 206580_s_at EFEMP2 NM_016938 EGF-containing fibulin-like extracellular matrix protein 2 206715_at TFEC NM_012252 transcription factor EC 206834_at HBD NM_000519 hemoglobin, delta 206968_s_at NFRKB NM_006165 nuclear factor related to kappaB binding protein 207075_at NLRP3 NM_004895 NLR family, pyrin domain containing 3 207078_at MED6 NM_005466 mediator complex subunit 6 207113_s_at TNF NM_000594 tumor necrosis factor (TNF superfamily, member 2) 207164_s_at ZNF238 NM_006352 zinc finger protein 238 207233_s_at MITF NM_000248 microphthalmia-associated transcription factor 207416_s_at NFATC3 NM_004555 nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 3 207513_s_at ZNF189 NM_003452 zinc finger protein 189 207543_s_at P4HA1 NM_000917 procollagen-proline, 2-oxoglutarate 4- dioxygenase (proline 4-hydroxylase), alpha polypeptide I 207564_x_at OGT NM_003605 O-linked N-acetylglucosamine (GlcNAc) transferase (UDP-N- acetylglucosamine:polypeptide-N- acetylglucosaminyl transferase) 207971_s_at CEP68 NM_015147 centroso al protein 68 kDa 208104_s_at TSC22D4 NM_030935 TSC22 domain family, member 4. 208121_s_at PTPRO NM_002848 protein tyrosine phosphatase, receptor type, O 208161_s_at ABCC3 NM_020037 ATP-binding cassette, sub-family C (CFTR/MRP), member 3 208269_s_at ADAM28 NM_021777 ADAM metallopeptidase domain 28 208309_s_at MALT1 NM_006785 mucosa associated lymphoid tissue lymphoma translocation gene 1 208527_x_at HIST1H2BE NM_003523 hitone cluster 1, H2be 208579_x_at H2BFS NM_017445 H2B histone family, member S 208635_x_at NACA BF976260 nascent polypeptide-associated complex alpha subunit 208659_at CLIC1 AF034607 chloride intracellular channel 1 208680_at PRDX1 L19184 peroxiredoxin 1 208749_x_at FLOT1 AF085357 flotillin 1 208771_s_at LTA4H J02959 leukotriene A4 hydrolase 208780_x_at VAPA AF154847 VAMP (vesicle-associated membrane protein)- associated protein A, 33 kDa 208798_x_at GOLGA8A AF204231 golgi autoantigen, golgin subfamily a, 8A 208805_at PSMA6 BC002979 proteasome (prosome, macropain) subunit, alpha type, 6 208868_s_at GABARAPL1 BF125756 GABA(A) receptor-associated protein like 1 208903_at RPS28 BF431363 ribosomal protein S28 208921_s_at SRI L12387 sorcin 208923_at CYFIP1 BC005097 cytoplasmic FMR1 interacting protein 1 208946_s_at BECN1 AF139131 beclin 1 (coiled-coil, myosin-like BCL2 interacting protein) 208962_s_at FADS1 BE540552 fatty acid desaturase 1 209040_s_at PSMB8 U17496 proteasome (prosome, macropain) subunit, beta type, 8 (large multifunctional peptidase 7) 209067_s_at HNRPDL D89092 heterogeneous nuclear ribonucleoprotein D-like 209072_at MBP M13577 myelin basic protein 209099_x_at JAG1 U73936 jagged 1 (Alagille syndrome) 209124_at MYD88 U70451 myeloid differentiation primary response gene (88) 209180_at RABGGTB U49245 Rab geranylgeranyltransferase, beta subunit 209191_at TUBB6 BC002654 tubulin, beta 6 209212_s_at KLF5 AB030824 Kruppel-like factor 5 (intestinal) 209218_at SQLE AF098865 squalene epoxidase 209236_at SLC23A2 AL389886 solute carrier family 23 (nucleobase transporters), member 2 209251_x_at TUBA1C BC004949 tubulin, alpha 1c 209259_s_at SMC3 AF020043 structural maintenance of chromosomes 3 209269_s_at SYK AW450910 spleen tyrosine kinase 209330_s_at HNRPD D55674 heterogeneous nuclear ribonucleoprotein D (AU- rich element RNA binding protein 1, 37 kDa) 209339_at SIAH2 U76248 seven in absentia homolog 2 (Drosophila) 209430_at BTAF1 AJ001017 BTAF1 RNA polymerase II, B-TFIID transcription factor-associated, 170kDa (Mott homolog, S. cerevisiae) 209675_s_at HNRPUL1 BC004242 heterogeneous nuclear ribonucleoprotein U-like 1 209684_at RIN2 AL136924 Ras and Rab interactor 2 209806_at HIST1H2BK BC000893 histone cluster 1, H2bk 209840_s_at LRRN3 AI221950 leucine rich repeat neuronal 3 209870_s_at APBA2 AW571582 amyloid beta (A4) precursor protein-binding, family A member 2 (X11-like) 209892_at FUT4 AF305083 fucosyltransferase 4 (alpha (1,3) fucosyltransferase, myeloid-specific) 209906_at C3AR1 U62027 complement component 3a receptor 1 210022_at PCGF1 BC004952 polycomb group ring finger 1 210061_at ZNF589 AF114817 zinc finger protein 589 210145_at PLA2G4A M68874 phospholipase A2, group IVA (cytosolic, calcium- dependent) 210156_s_at PCMT1 D25547 protein-L-isoaspartate (D-aspartate) O- methyltransferase 210166_at TLR5 AF051151 toll-like receptor 5 210434_x_at JTB AF151056 jumping translocation breakpoint 210644_s_at LAIR1 AF109683 leukocyte-associated immunoglobulin-like receptor 1 210648_x_at SNX3 AB047360 sorting nexin 3 210875_s_at ZEB1 U12170 zinc finger E-box binding homeobox 1 211047_x_at AP2S1 BC006337 adaptor-related protein complex 2, sigma 1 subunit 211058_x_at TUBA1B BC006379 tubulin, alpha 1b 211185_s_at SF3B1 AF130099 splicing factor 3b, subunit 1, 155 kDa 211272_s_at DGKA AF064771 diacylglycerol kinase, alpha 80 kDa 211323_s_at ITPR1 L38019 inositol 1,4,5-triphosphate receptor, type 1 211383_s_at WDR37 AL136827 WD repeat domain 37 211429_s_at SERPINA1 AF119873 serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 1 211506_s_at IL8 AF043337 interleukin 8 211546_x_at SNCA L36674 synuclein, alpha (non A4 component of amyloid precursor) 211684_s_at DYNC1I2 AF250307 dynein, cytoplasmic 1, intermediate chain 2 211729_x_at BLVRA BC005902 biliverdin reductase A 211856_x_at CD28 AF222341 CD28 molecule 211946_s_at BAT2D1 AL096857 BAT2 domain containing 1 211965_at ZFP36L1 BE620915 zinc finger protein 36, C3H type-like 1 212030_at RBM25 BG251218 RNA binding motif protein 25 212042_x_at hCG_31916///RPL7 BG389744 ribosomal protein L7///hCG31916 212132_at LSM14A AL117499 LSM14A, SCD6 homolog A (S. cerevisiae) 212213_x_at OPA1 AB011139 optic atrophy 1 (autosomal dominant) 212299_at NEK9 AL117502 NIMA (never in mitosis gene a)- related kinase 9 212331_at RBL2 X76061 retinoblastoma-like 2 (p130) 212334_at GNS BE880245 glucosamine (N-acetyl)-6-sulfatase (Sanfilippo disease IIID) 212406_s_at PCMTD2 AB028973 protein-L-isoaspartate (D-aspartate) O- methyltransferase domain containing 2 212455_at YTHDC1 N36997 YTH domain containing 1 212543_at AIM1 083115 absent in melanoma 1 212658_at LHFPL2 N66633 lipoma HMGIC fusion partner-like 2 212663_at FKBP15 AB014574 FK506 binding protein 15, 133 kDa 212769_at TLE3 AI567426 transducin-like enhancer of split 3 (E(sp1) homolog, Drosophila) 212820_at DMXL2 AB020663 Dmx-like 2 212932_at RAB3GAP1 AK022494 RAB3 GTPase activating protein subunit 1 (catalytic) 212989_at SGMS1 AI377497 sphingomyelin synthase 1 212997_s_at TLK2 AU151689 tousled-like kinase 2 213021_at GOSR1 AI741876 golgi SNAP receptor complex member 1 213152_s_at SFRS2B AI343248 splicing factor, arginine/serine-rich 2B 213205_s_at RAD54L2 AU159543 RAD54-like 2 (S. cerevisiae) 213218_at ZNF187 AV705032 zinc finger protein 187 213266_at 76P BF592982 Gamma tubulin ring complex protein (76p gene) 213302_at PFAS AL044326 phosphoribosylformylglycinamidine synthase (FGAR amidotransferase) 213335_s_at ST3GAL6 AK001922 ST3 beta-galactoside alpha-2,3-sialyltransferase 6 213397_x_at RNASE4 AI761728 ribonuclease, RNase A family, 4 213459_at RPL37A AU155515 ribosomal protein L37a 213494_s_at YY1 AA748649 YY1 transcription factor 213540_at HSD17B8 AL031228 hydroxysteroid (17-beta) dehydrogenase 8 213693_s_at MUC1 AI610869 mucin 1, cell surface associated 213827_at SNX26 AL137579 sorting nexin 26 213877_x_at TCEB2 AI568533 transcription elongation factor B (SIII), polypeptide 2 (18 kDa, elonqin B) 214045_at LIAS BF056778 lipoic acid synthetase 214057_at MCL1 H71805 Myeloid cell leukemia sequence 1 (BCL2- related) 214330_at ATPAF2 AF070584 ATP synthase mitochondrial F1 complex assembly factor 2 214364_at MTERFD2 W84525 MTERF domain containing 2 214430_at GLA NM_000169 galactosidase, alpha 214511_x_at FCGR1B L03419 Fc fragment of IgG, high affinity Ib, receptor (CD64) 214629_x_at RTN4 AF320999 reticulon 4 214683_s_at CLK1 A1251890 CDC-like kinase 1 214820_at BRWD1 AJ002572 bromodomain and WD repeat domain containing. 1 214853_s_at SHC1 A1091079 SHC (Src homology 2 domain containing) transforming protein 1 214931_s_at SRPK2 AC005070 SFRS protein kinase 2 214953_s_at APP X06989 amyloid beta (A4) precursor protein (peptidase nexin-11, Alzheimer disease) 215009_s_at SEC31A U92014 SEC31 homolog A (S. cerevisiae) 215049_x_at CD163 Z22969 CD163 molecule 215273_s_at TADA3L AK024982 transcriptional adaptor 3 (NGG1 homolog, yeast)-like 215293_s_at FRAG1 AL049261 FGF receptor activating protein 1 215567_at FCF1 AU144919 FCF1 small subunit (SSU) processome component homolog (S. cerevisiae) 215997_s_at CUL4B AV694732 cullin 4B 216484_x_at HDGF L24521 Hepatoma-derived growth factor (high-mobility group protein 1-like) 216950_s_at FCGR1A X14355 Fc fragment of IgG, high affinity la, receptor (CD64) 217383_at PGK1 S81916 Phosphoglycerate kinase 1 217403_s_at ZNF227 AC074331 zinc finger protein 227 217466_x_at LOC400963/// L48784 ribosomal protein S2///hypothetical gene LOC440589/// supported by AB082925; BC019021; NM LOC441013/// 002952 III similar to ribosomal protein S2/// LOC645173/// hypothetical LOC645173 LOC646294/// LOC650901/// LOC729274/// RPS2 217769_s_at POMP NM_015932 proteasome maturation protein 217778_at SLC39A1 NM_014437 solute carrier family 39 (zinc transporter), member 1 217824_at UBE2J1 AW500009 ubiquitin-conjugating enzyme E2, J1 (UBC6 homolog, yeast) 217987_at ASNSD1 NM_019048 asparagine synthetase domain containing 1 217995_at SQRDL NM_021199 sulfide quinone reductase-like (yeast) 218012_at TSPYL2 NM_022117 TSPY-like 2 218040_at PRPF38B NM_018061 PRP38 pre-mRNA processing factor 38 (yeast) domain containing B 218065_s_at TMEM9B NM_020644 TMEM9 domain family, member B 218091_at HRB AI989512 HIV-1 Rev binding protein 218125_s_at CCDC25 NM_018246 coiled-coil domain containing 25 218127_at NFYB AI804118 nuclear transcription factor Y, beta 218143_s_at SCAMP2 NM_005697 secretory carrier membrane protein 2 218206_x_at SCAND1 NM_016558 SCAN domain containing 1 218289_s_at UBE1DC1 NM_024818 ubiquitin-activating enzyme E1-domain containing 1 218325_s_at DIDO1 NM_022105 death inducer-obliterator 1 218351_at COMMD8 NM_017845 COMM domain containing 8 218499_at RP6-213H19.1 NM_016542 serine/threonine protein kinase MST4 218627_at DRAM NM_018370 damage-regulated autophaqy modulator 218718_at PDGFC NM_016205 platelet derived growth factor C 218732_at PTRH2 NM_016077 peptidyl-tRNA hydrolase 2 218845_at DUSP22 NM_020185 dual specificity phosphatase 22 218962_s_at TMEM168 NM_022484 transmembrane protein 168 219130_at CCDC76 NM_019083 coiled-coil domain containing 76 219316_s_at F VCR2 NM_017791 feline leukemia virus subgroup C cellular receptor family, member 2 219343_at CDC37L1 NM_017913 cell division cycle 37 homolog (S. cerevisiae)- like 1 219358_s_at CENTA2 NM_018404 centaurin, alpha 2 219418_at NHEJ1 NM_024782 nonhomologous end-joining factor 1 219507_at RSRC1 NM_016625 arginine/serine-rich coiled-coil 1 219765_at ZNF329 NM_024620 zinc finger protein 329 219787_s_at ECT2 NM_018098 epithelial cell transforming sequence 2 oncogene 219822_at MTRF1 NM_004294 mitochondrial translational release factor 1 219826_at ZNF419 NM_024691 zinc finger protein 419 219952_s_at MCOLN1 NM_020533 mucolipin 1 220044_x_at CROP NM_016424 cisplatin resistance-associated overexpressed protein 220146_at TLR7 NM_016562 toll-like receptor 7 220160_s_at KPTN NM_007059 kaptin (actin binding protein) 220386_s_at EML4 NM_019063 echinoderm microtubule associated protein like 4 220578_at ADAMTSL4 NM_025008 ADAMTS-like 4 220605_s_at SIRT2 NM_012237 sirtuin (silent mating type information regulation 2 homolog) 2 (S. cerevisiae) 220610_s_at LRRFIP2 NM_006309 leucine rich repeat (in FLII) interacting protein 2 220690_s_at DHRS7B NM_015510 dehydrogenase/reductase (SDR family) member 7B 220750_s_at LEPRE1 NM_022356 leucine proline-enriched proteoglycan (leprecan) 1 220865_s_at PDSS1 NM_014317 prenyl (decaprenyl) diphosphate synthase, subunit 1 220974_x_at SFXN3 NM_030971 sideroflexin 3 221011_s_at LBH NM_030915 limb bud and heart development homolog (mouse) 22 206_at PMS2 NM_024521 PMS2 postmeiotic segregation increased 2 (S. cerevisiae) 221264_s_at TARDBP NM_031214 TAR DNA binding protein 221428_s_at TBL1XR1 NM_030921 transducin (beta)-like 1X-linked receptor 1 221449_s_at ITFG1 NM_030790 integrin alpha FG-GAP repeat containing 1 221580_s_at JOSD3 BC001972 Josephin domain containing 3 221601_s_at FAIM3 A1084226 Fas apoptotic inhibitory molecule 3 221647_s_at RIC8A AL136935 resistance to inhibitors of cholinesterase 8 homolog A (C. elegans) 221731_x_at VCAN BF218922 versican 221757_at PIK3IP1 BE042976 phosphoinositide-3-kinase interacting protein 1 221841_s_at KLF4 BF514079 Kruppel-like factor 4 (gut) 221868_at PAIP2B AB032981 poly(A) binding protein interacting protein 2B 221960_s_at RAB2A A1189609 RAB2A, member RAS oncoqene family 222217_s_at SLC27A3 BC003654 solute carrier family 27 (fatty acid transporter), member 3 222231_s_at LRRC59 AK025328 leucine rich repeat containing 59 222574_s_at DHX40 BF431360 DEAH (Asp-Glu-Ala-His) box polypeptide 40 222605_at RCOR3 A1807073 REST corepressor 3 222651_s_at TRPS1 BF701166 trichorhinophalangeal syndrome I 222670_s_at MAFB AW135013 v-maf musculoaponeurotic fibrosarcoma oncogene homolog B (avian) 222688_at PHCA R12678 phytoceramidase, alkaline 222700_at ARL6IP2 AV700003 ADP-ribosylation factor-like 6 interacting protein 2 222753_s_at SPCS3 AL136660 signal peptidase complex subunit 3 homolog (S. cerevisiae) 222757_s_at ZAK AB030034 sterile alpha motif and leucine zipper containing kinase AZK 222774_s_at NETO2 AI335263 neuropilin (NRP) and tolloid (TLL)-like 2 222884_at ZNF346 AI830579 zinc finger protein 346 222980_at RAB10 AL136650 RAB10, member RAS oncogene family 222982_x_at SLC38A2 AF298897 solute carrier family 38, member 2 223023_at BET1L BC000688 blocked early in transport 1 homolog (S. cerevisiae)-like 223064_at RNF181 AF151072 ring finger protein 181 223158_s_at NEK6 BE616825 NIMA (never in mitosis gene a)-related kinase 6 223380_s_at LATS2 AF207547 LATS, large tumor suppressor, homolog 2 (Drosophila) 223444_at SENP7 AL136599 SUMO1/sentrin specific peptidase 7 223465_at COL4A3BP BE967275 collagen, type IV, alpha 3 (Goodpasture antigen) binding protein 223590_at ZNF700 AL136732 zinc finger protein 700 223686_at TPK1 AB028138 thiamin pyrophosphokinase 1 223801_s_at APOL4 AY014914 apolipoprotein L, 4 223922_x_at MS4A6A AB013104 membrane-spanning 4-domains, subfamily A, member 6A 223982_s_at PNPLA8 AB041261 patatin-like phospholipase domain containing 8 224046_s_at PDE7A U67932 phosphodiesterase 7A 224374_s_at EMILIN2 AF270513 elastin microfibril interfacer 2 224387_at COMMD5 AF290195 COMM domain containing 5 224439_x_at RNF7 BC005966 ring finger protein 7 224518_s_at ZNF559 BC006436 zinc finger protein 559 224582_s_at NUCKS1 H09085 nuclear casein kinase and cyclin-dependent kinase substrate 1 224591_at HP1BP3 AK023129 heterochromatin protein 1, binding protein 3 224726_at MIB1 W80418 mindbomb homolog 1 (Drosophila) 224818_at SORT1 BE622952 sortilin 1 224917_at MIRN21 BF674052 microRNA 21 224918_x_at MGST1 AI220117 microsomal glutathione S-transferase 1 224928_at SETD7 AK024846 SET domain containing (lysine- methyltransferase) 7 225059_at AGTRAP BE875567 angiotensin II receptor-associated protein 225064_at RABEP1 R60018 rabaptin, RAB GTPase binding effector protein 1 225107_at HNRNPA2B1 A1963008 heterogeheous nuclear ribonucleoprotein A2/B1 225188_at RAPH1 AA194149 Ras association (RaIGDS/AF-6) and pleckstrin homology domains 1 225341_at MTERFD3 BF697312 MTERF domain containing 3 225358_at DNAJCI9 A1003794 DnaJ (Hsp40) homolog, subfamily C, member 19 225365_at ZDHHC20 BG249221 zinc finger, DHHC-type containing 20 225388_at TSPAN5 A1928507 tetraspanin 5 225456_at MED1 A1708776 mediator complex subunit 1 225763_at RCSD1 A1659418 RCSD domain containing 1 225844_at POLE4 NM_019896 polymerase (DNA-directed), epsilon 4 (p12 subunit) 225866_at BXDC1 AA976536 brix domain containing 1 225870_s_at TRAPPC5 BF569208 trafficking protein particle complex 5 226000_at CTTNBP2NL A1423056 CTTNBP2 N-terminal like 226030_at ACADSB BE897866 acyl-Coenzyme A dehydrogenase, short/branched chain 226042_at EDC3 AL563608 enhancer of mRNA decapping 3 homolog (S. cerevisiae) 226059_at TOMM4OL AK022832 translocase of outer mitochondrial membrane 40 homolog (yeast)-like 226115_at AHCTF1 A1138934 AT hook containing transcription factor 1 226127_at ALKBH3 BF062547 alkB, alkylation repair homoloq 3 (E. coli) 226218_at IL7R BE217880 interleukin 7 receptor 226220_at METTL9 BE551054 Methyltransferase like 9 226323_at CCDC16 AA398517 coiled-coil domain containing 16 226353_at SPPL2A A1674647 signal peptide peptidase-like 2A 226428_at TNPO2 A1885873 transportin 2 (importin 3, karyopherin beta 2b) 226459_at PIK3AP1 AW575754 phosphoinositide-3-kinase adaptor protein 1 226503_at RIF1 BE504653 RAP1 interacting factor homolog (yeast) 226683_at SNAG1 AU146771 Sorting nexin associated golgi protein 1 226718_at AMIGO1 AA001423 adhesion molecule with Ig-like domain 1 226763_at SESTD1 AW409611 SEC14 and spectrin domains 1 226836_at SFT2D1 AA044813 SFT2 domain containing 1 227020_at YPEL2 BE502982 yippee-like 2 (Drosophila) 227114_at RNF214 BG435876 ring finger protein 214 227149_at TNRC6C AB046802 trinucleotide repeat containing 6C 227173_s_at BACH2 AW450901 BTB and CNC homology 1, basic leucine zipper transcription factor 2 227213_at ADAT2 AA706895 adenosine deaminase, tRNA-specific 2, TAD2 homolog (S. cerevisiae) 227374_at EARS2 AA833716 glutamyl-tRNA synthetase 2, mitochondrial (putative) 227517_s_at GAS5 A1056992 growth arrest-specific 5 227558_at CBX4 A1570531 chromobox homolog 4 (Pc class homolog, Drosophila) 227560_at SFXN2 AL530504 sideroflexin 2 227722_at RPS23 AW043594 ribosomal protein S23 227990_at SLU7 AA843238 SLU7 splicing factor homolog (S. cerevisiae) 228012_at MATR3 N53862 Matrin 3 228170_at 0 G1 AL355743 oligodendrocyte transcription factor 1 228176_at EDG3 AA534817 endothelial differentiation, sphingolipid G-protein- coupled receptor, 3 228234_at TICAM2 A1423165 toll-like receptor adaptor molecule 2 228370_at SNRPN BF114870 Small nuclear ribonucleoprotein polypeptide N 228549_at TMEM63A A1491983 Transmembrane protein 63A 228630_at ZNF84 W92744 Zinc finger protein 84 228831_s_at GNG7 AL039870 guanine nucleotide binding protein (G protein), gamma 7 229307_at ANKRD28 N32051 ankyrin repeat domain 28 229421_s_at FLJ20273 BF435329 RNA-binding protein 229509_at MFSD8 AA534752 major facilitator superfamily domain containing 8 229854_at OBSCN AW614056 obscurin, cytoskeletal calmodulin and titin- interacting RhoGEF 229982_at QSER1 AW195525 glutamine and serine rich 1 230265_at SEL1L BE671138 Sel-1 suppressor of lin-12-like (C. elegans) 230320_at TBRG1 AW291696 transforming growth factor beta regulator 1 230408_at PCGF3 BG231712 Polycomb group ring finger 3 230480_at PIWIL4 A1808955 piwi-like 4 (Drosophila) 230837_at LOC647500 N67108 similar to phosphodiesterase 4D interacting protein isoform 1 230852_at STAC3 AW663959 SH3 and cysteine rich domain 3 230922_x_at FUNDC2 H09739 FUN14 domain containing 2 231283_at MGAT4A AW271609 mannosyl (alpha-1,3-)-glycoprotein beta-1,4-N- acetylglucosaminyltransferase, isozyme A 231697_s_at TMEM49 AV660825 Transmembrane protein 49 231836_at HKR1 BC004513 GLI-Kruppel family member HKR1 231843_at DDX55 AB046815 DEAD (Asp-Glu-Ala-Asp) box polypeptide 55 231845_at AARS2 AI721172 alanyl-tRNA synthetase 2, mitochondrial (putative) 231904_at U2AF1 AU122448 U2 small nuclear RNA auxiliary factor 1 231914_at NUDT14 W24623 nudix (nucleoside diphosphate linked moiety X)- type motif 14 232636_at SLITRK4 AL080239 SLIT and NTRK-like family, member 4 232851_at FBXO3 AL162053 F-box protein 3 233019_at CNOT7 AU145061 CCR4-NOT transcription complex, subunit 7 233169_at ZNF350 AU145915 zinc finger protein 350 234013_at TRA@ AE000659 T cell receptor alpha locus///Clone PSA.S.31 T- cell receptor alpha chain 234311_s_at GTPBP10 AC006153 GTP-bindinq protein 10 (putative) 234339_s_at GLTSCR2 AF296124 glioma tumor suppressor candidate region gene 2 234464_s_at EME1 AK021607 essential meiotic endonuclease 1 homolog 1 (S. pombe) 234733_s_at FANCM AK001672 Fanconi anemia, complementation group M 235024_at PHF17 AI868315 PHD finger protein 17 235067_at MKLN1 D81987 muskelin 1, intracellular mediator containing kelch motifs 235200_at ZNF561 AL135342 zinc finger protein 561 235359_at LRRC33 AA534416 leucine rich repeat containing 33 235593_at ZEB2 AL546529 zinc finger E-box binding homeobox 2 235610_at ALKBH8 AI590659 alkB, alkylation repair homolog 8 (E. coli) 235623_at ELP2 BF526230 Elongation protein 2 homoloq (S. cerevisiae) 235690_at ZNF594 AA872562 zinc finger protein 594 237504_at INTS10 AW002398 integrator complex subunit 10 238429_at TMEM71 AI342543 transmembrane protein 71 238513_at PRRG4 BF905445 Proline rich Gla (G-carboxyglutamic acid) 4 (transmembrane) 238736_at REV3L AA805939 REV3-like, catalytic subunit of DNA polymerase zeta (yeast) 238823_at FMNL3 AA481044 formin-like 3 238909_at S100A10 BF126155 S100 calcium binding protein A10 239108_at MLSTD1 H16791 Male sterility domain containing 1 239897_at BCLAF1 AW152620 BCL2-associated transcription factor 1 241368_at LSDP5 AI190693 lipid storage droplet protein 5 241704_x_at ZNF320 AI025436 zinc finger protein 320 241706_at CPNE8 AA431782 copine VIII 241731_x_at ZNF440 AA883653 zinc finger protein 440 242197_x_at CD36 W95035 CD36 molecule (thrombospondin receptor) 242561_at IPO9 AW075415 importin 9 242569_at STAM2 N57099 Signal transducing adaptor molecule (SH3 domain and ITAM motif) 2 242669_at UFM1 BF514975 Ubiquitin-fold modifier 1 243982_at KLHL28 AA455180 Kelch-like 28 (Drosophila) 244038_at WDR89 AW069315 WD repeat domain 89 244654_at MYO1G BE646398 myosin IG 244698_at CDRT4 AW297656 CMT1A duplicated region transcript 4 36566_at CTNS AJ222967 cystinosis, nephropathic 37549 _g_at BBS9 U87408 Bardet-Biedl syndrome 9 48659_at RP5-107789.4 W60802 invasion inhibitory protein 45 56829_at NIBP H61826 NIK and IKK{beta} binding protein 64486_at CORO1B AI341234 coronin, actin binding protein, 1B 65493_at HEATR6 AA555088 HEAT repeat containing 6 AFFX- GAPDH NM_002046 glyceraldehyde-3-phosphate dehydrogenase HUMGAPDH/ M331973_at

TABLE 3 Extreme Extreme control- NYHA I-II- directional directional fold- Statistical Maximum Average fold-change change significance overall fold-change Average fold- observed Average observed of accuracy of gene change (Extreme fold-change (Extreme differential classification expression expression at NYHA expression at Control/ Affymetrix Probe expression power (NYHA I-II/ sensitivity = I-II/average specificity = average set ID Gene symbol (p-value) (ROC AUC) Control) 0.6 Control) 0.6 Control) 1552630_a_at SRCAP 2.52E−03 0.701 0.831 0.800 0.415 1.032 1.417 1554149_at CLDND1 2.85E−02 0.681 0.907 0.852 0.587 1.048 1.291 1554606_at CCDC100 7.47E−03 0.710 0.860 0.811 0.423 1.100 1.175 1555630_a_at RAB34 2.76E−03 0.731 1.277 1.115 2.496 1.044 0.591 1555963_x_at B3GNT7 1.34E−03 0.705 1.206 1.119 1.950 1.105 0.719 1556113_at DKFZp451A211 1.63E−02 0.679 1.118 1.065 1.523 1.060 0.722 1556283_s_at FGFR1OP2 3.82E−03 0.732 1.194 1.122 1.665 1.028 0.634 1556864_at TECT1 1.30E−03 0.736 0.849 0.866 0.569 1.010 1.424 1557066_at LUC7L 2.91E−02 0.697 0.873 0.840 0.474 1.064 1.349 1558277_at ZNF740 1.18E−03 0.741 1.326 1.149 2.721 1.038 0.648 1558755_x_at ZNF763 3.51E−03 0.717 0.816 0.736 0.434 1.118 1.312 1561146_at VPS35 9.85E−04 0.736 0.789 0.773 0.364 1.030 1.929 1564962_at ZNF92 4.83E−04 0.791 0.799 0.740 0.535 1.019 1.521 1568815_a_at DDX50 1.56E−02 0.709 0.836 0.804 0.449 1.010 2.085 200007_at SRP14 9.03E−04 0.756 1.080 1.062 1.268 1.039 0.854 200059_s_at RHOA 1.12E−03 0.743 1.068 1.044 1.229 1.015 0.867 200633_at UBB 4.40E−03 0.735 1.102 1.089 1.460 1.027 0.785 200650_s_at LDHA 2.14E−02 0.649 1.099 1.043 1.560 1.052 0.736 200672_x_at SPTBN1 4.56E−02 0.670 0.893 0.787 0.523 1.030 1.532 200713_s_at MAPRE1 2.56E−04 0.778 1.106 1.069 1.415 1.009 0.906 200822_x_at TPI1 3.61E−03 0.718 1.102 1.077 1.387 1.009 0.723 200829_x_at ZNF207 1.69E−04 0.780 1.147 1.102 1.426 1.042 0.812 200839_s_at CTSB 3.74E−03 0.744 1.199 1.136 1.939 1.034 0.546 200932_s_at DCTN2 3.28E−03 0.723 1.069 1.039 1.506 1.024 0.881 200950_at ARPC1A 7.18E−04 0.759 1.102 1.080 1.342 1.009 0.880 201075_s_at SMARCC1 7.66E−05 0.801 0.874 0.839 0.717 1.024 1.246 201098_at COPB2 1.20E−03 0.750 1.079 1.045 1.347 1.020 0.897 201105_at LGALS1 1.17E−03 0.778 1.339 1.256 2.357 1.041 0.513 201172_x_at ATP6V0E1 5.94E−03 0.699 1.075 1.048 1.284 1.030 0.865 201186_at LRPAP1 2.18E−02 0.660 1.119 1.033 1.615 1.027 0.783 201193_at IDH1 1.59E−04 0.756 1.192 1.124 1.634 1.078 0.784 201198_s_at PSMD1 8.47E−04 0.769 1.138 1.120 1.517 1.051 0.736 201220_x_at CTBP2 4.25E−02 0.665 1.085 1.053 1.498 1.028 0.796 201234_at ILK 8.39E−05 0.790 1.137 1.082 1.696 1.015 0.867 201357_s_at SF3A1 5.49E−05 0.813 0.847 0.830 0.582 1.002 1.293 201363_s_at IVNS1ABP 2.68E−04 0.771 0.851 0.846 0.550 1.016 1.300 201400_at PSMB3 4.52E−03 0.718 1.106 1.067 1.541 1.011 0.820 201422_at IFI30 3.74E−03 0.714 1.151 1.090 1.651 1.026 0.686 201426_s_at VIM 9.14E−03 0.748 1.092 1.055 1.367 1.004 0.847 201453_x_at RHEB 1.65E−03 0.738 1.084 1.064 1.331 1.025 0.810 201470_at GSTO1 2.91E−03 0.736 1.171 1.080 2.090 1.005 0.770 201527_at ATP6V1F 4.72E−03 0.713 1.093 1.068 1.414 1.037 0.839 201536_at DUSP3 2.41E−02 0.644 1.160 1.044 2.261 1.035 0.742 201554_x_at GYG1 4.62E−02 0.638 1.140 1.018 2.004 1.011 0.674 201556_s_at VAMP2 3.34E−04 0.771 0.810 0.755 0.494 0.985 1.523 201576_s_at GLB1 8.64E−03 0.720 1.108 1.060 1.374 1.022 0.743 201590_x_at ANXA2 1.98E−04 0.799 1.259 1.172 1.807 1.062 0.631 201628_s_at RRAGA 2.82E−03 0.744 1.086 1.047 1.318 1.029 0.842 201900_s_at AKR1A1 2.20E−03 0.729 1.158 1.069 1.799 1.023 0.770 201945_at FURIN 7.29E−03 0.685 0.846 0.808 0.464 1.023 1.482 202068_s_at LDLR 9.51E−03 0.708 1.352 1.149 3.500 1.029 0.406 202138_x_at JTV1 1.35E−03 0.726 1.135 1.064 1.523 1.048 0.776 202185_at PLOD3 5.67E−04 0.778 1.135 1.107 1.479 1.023 0.797 202201_at BLVRB 1.21E−02 0.731 1.196 1.081 2.124 1.001 0.675 202249_s_at WDR42A 1.48E−02 0.695 0.925 0.875 0.748 1.030 1.224 202252_at RAB13 1.20E−02 0.703 1.374 1.125 6.988 1.083 0.711 202428_x_at DBI 3.93E−05 0.810 1.174 1.121 1.569 1.038 0.807 202445_s_at NOTCH2 1.12E−02 0.714 0.874 0.831 0.551 1.060 1.223 202461_at EIF2B2 5.63E−04 0.803 1.195 1.151 1.755 1.059 0.653 202522_at PITPNB 1.15E−03 0.762 1.094 1.072 1.291 1.017 0.822 202523_s_at SPOCK2 1.53E−02 0.670 0.834 0.630 0.347 1.065 1.476 202623_at EAPP 3.76E−04 0.763 0.917 0.896 0.756 1.012 1.174 202652_at APBB1 1.06E−02 0.719 0.862 0.805 0.403 1.019 1.429 202724_s_at FOXO1 7.97E−03 0.668 0.881 0.857 0.560 0.997 1.437 202778_s_at ZMYM2 1.35E−03 0.741 0.907 0.874 0.640 1.026 1.162 202928_s_at PHF1 3.96E−04 0.769 0.852 0.808 0.460 1.013 1.320 202944_at NAGA 1.96E−03 0.740 1.226 1.152 1.815 1.008 0.676 203003_at MEF2D 3.66E−04 0.799 0.835 0.820 0.603 0.978 1.416 203127_s_at SPTLC2 2.12E−03 0.737 1.199 1.125 1.838 1.058 0.719 203137_at WTAP 7.00E−03 0.697 0.929 0.903 0.744 1.030 1.177 203305_at F13A1 3.94E−02 0.644 1.306 1.066 3.596 1.052 0.534 203413_at NELL2 2.75E−02 0.699 0.799 0.658 0.309 1.017 1.764 203416_at CD53 4.36E−03 0.702 1.063 1.041 1.275 1.019 0.867 203534_at LSM1 1.23E−04 0.818 1.149 1.114 1.460 1.024 0.815 203759_at ST3GAL4 1.17E−02 0.710 0.768 0.713 0.417 1.066 2.047 203844_at VHL 1.12E−02 0.674 1.066 1.028 1.448 1.029 0.794 203880_at COX17 1.35E−03 0.741 1.167 1.090 1.714 1.046 0.695 203912_s_at DNASE1L1 1.75E−03 0.764 1.201 1.156 1.660 1.051 0.647 203939_at NT5E 8.38E−03 0.710 0.802 0.642 0.370 1.004 1.778 204050_s_at CLTA 1.90E−03 0.748 1.107 1.058 1.398 1.010 0.865 204099_at SMARCD3 8.10E−03 0.686 1.240 1.092 2.367 1.074 0.701 204243_at RLF 9.43E−03 0.701 1.122 1.084 1.534 1.064 0.752 204249_s_at LMO2 8.50E−03 0.749 1.162 1.130 1.884 1.014 0.804 204291_at ZNF518 4.67E−02 0.641 0.924 0.901 0.361 1.037 1.201 204401_at KCNN4 5.05E−03 0.709 0.828 0.723 0.283 1.040 1.629 204617_s_at ACD 3.92E−03 0.724 0.895 0.839 0.690 1.045 1.209 204645_at CCNT2 3.56E−04 0.758 0.886 0.870 0.556 1.009 1.238 204675_at SRD5A1 3.83E−04 0.788 1.321 1.159 2.286 1.037 0.572 204801_s_at DHRS12 1.62E−03 0.756 0.757 0.644 0.407 1.089 1.834 205235_s_at MPHOSPH1 3.01E−03 0.742 0.905 0.885 0.735 1.033 1.309 205254_x_at TCF7 3.47E−02 0.660 0.862 0.676 0.167 1.007 1.924 205256_at ZBTB39 4.74E−02 0.661 0.935 0.891 0.721 1.012 1.321 205550_s_at BRE 2.43E−02 0.674 1.057 1.025 1.234 1.023 0.835 206170_at ADRB2 4.22E−04 0.788 1.459 1.338 2.681 1.109 0.361 206182_at ZNF134 4.17E−02 0.660 0.925 0.882 0.680 1.026 1.305 206542_s_at SMARCA2 1.86E−03 0.731 0.900 0.872 0.706 1.015 1.228 206715_at TFEC 1.82E−02 0.678 1.269 1.104 2.537 1.068 0.516 206968_s_at NFRKB 3.47E−02 0.632 0.919 0.928 0.573 1.028 1.276 207078_at MED6 9.05E−03 0.688 0.887 0.826 0.442 1.048 1.304 207113_s_at TNF 5.32E−03 0.706 1.219 1.145 1.942 1.123 0.644 207164_s_at ZNF238 2.47E−03 0.714 0.845 0.792 0.260 1.008 1.390 207513_s_at ZNF189 4.39E−03 0.704 0.898 0.880 0.543 1.023 1.332 207543_s_at P4HA1 4.39E−02 0.669 1.099 1.054 1.625 0.985 0.746 208104_s_at TSC22D4 3.93E−04 0.748 0.869 0.860 0.565 1.027 1.257 208121_s_at PTPRO 4.15E−04 0.784 1.456 1.351 3.729 1.136 0.562 208161_s_at ABCC3 3.53E−04 0.778 1.465 1.187 4.485 1.068 0.473 208269_s_at ADAM28 2.06E−03 0.748 0.859 0.817 0.568 1.052 1.412 208659_at CLIC1 3.13E−02 0.683 1.054 1.040 1.342 0.987 0.890 208680_at PRDX1 1.37E−03 0.746 1.224 1.124 1.805 1.067 0.676 208771_s_at LTA4H 8.95E−03 0.690 1.244 1.116 2.001 1.055 0.567 208805_at PSMA6 1.50E−03 0.728 1.145 1.055 1.862 1.028 0.808 208868_s_at GABARAPL1 1.00E−04 0.769 0.834 0.787 0.443 1.053 1.171 208921_s_at SRI 1.71E−03 0.744 1.106 1.081 1.347 1.028 0.806 208923_at CYFIP1 1.02E−03 0.741 1.262 1.159 2.216 1.077 0.697 208946_s_at BECN1 1.90E−04 0.759 0.938 0.925 0.810 1.012 1.115 209040_s_at PSMB8 7.81E−04 0.763 1.135 1.071 1.991 1.018 0.853 209099_x_at JAG1 2.79E−02 0.661 1.201 1.043 3.100 1.034 0.692 209124_at MYD88 8.80E−03 0.676 1.085 1.072 1.422 0.999 0.882 209191_at TUBB6 4.39E−02 0.613 1.281 0.915 2.538 1.061 0.615 209218_at SQLE 2.18E−03 0.719 1.389 1.143 2.894 1.085 0.578 209236_at SLC23A2 5.80E−03 0.682 0.901 0.863 0.604 1.040 1.181 209251_x_at TUBA1C 1.78E−02 0.687 1.090 1.052 1.375 1.045 0.809 209269_s_at SYK 7.21E−04 0.746 0.823 0.790 0.469 1.055 1.675 209675_s_at HNRPUL1 1.14E−03 0.742 0.870 0.856 0.599 1.036 1.341 209684_at RIN2 2.06E−02 0.684 1.244 1.027 2.378 1.004 0.558 209892_at FUT4 5.23E−04 0.754 1.303 1.131 4.088 1.052 0.714 210022_at PCGF1 6.75E−03 0.692 0.936 0.915 0.745 1.001 1.265 210145_at PLA2G4A 1.35E−03 0.753 1.319 1.263 2.076 1.133 0.674 210156_s_at PCMT1 4.98E−03 0.698 1.111 1.077 1.489 1.060 0.835 210434_x_at JTB 1.84E−04 0.790 1.097 1.063 1.266 1.044 0.845 210644_s_at LAIR1 8.12E−05 0.791 1.341 1.177 3.053 1.031 0.696 210648_x_at SNX3 2.36E−04 0.770 1.134 1.086 1.549 1.002 0.854 210875_s_at ZEB1 6.08E−05 0.782 0.768 0.745 0.388 1.005 1.535 211047_x_at AP2S1 4.36E−04 0.780 1.136 1.112 1.383 1.023 0.779 211058_x_at TUBA1B 1.56E−02 0.688 1.059 1.037 1.262 1.019 0.857 211185_s_at SF3B1 3.75E−03 0.734 0.943 0.933 0.791 1.025 1.150 211323_s_at ITPR1 7.88E−03 0.680 0.873 0.818 0.535 1.063 1.345 211383_s_at WDR37 1.13E−03 0.744 1.118 1.076 1.404 1.056 0.826 211506_s_at IL8 4.32E−05 0.803 0.495 0.284 0.059 1.059 2.135 211684_s_at DYNC1I2 1.57E−03 0.754 1.182 1.135 1.720 1.047 0.655 211729_x_at BLVRA 1.88E−03 0.722 1.250 1.075 2.037 1.038 0.607 211856_x_at CD28 3.85E−02 0.697 0.839 0.687 0.250 1.099 1.625 211946_s_at BAT2D1 4.44E−03 0.669 0.933 0.889 0.736 1.038 1.095 211965_at ZFP36L1 1.31E−03 0.729 0.737 0.634 0.361 0.965 1.774 212030_at RBM25 2.89E−03 0.718 0.897 0.875 0.698 1.012 1.292 212132_at LSM14A 3.39E−03 0.713 0.925 0.897 0.688 1.017 1.224 212213_x_at OPA1 3.49E−04 0.784 1.146 1.082 1.614 1.015 0.810 212299_at NEK9 3.00E−02 0.665 1.097 1.052 1.461 1.042 0.691 212334_at GNS 1.58E−02 0.708 1.118 1.065 1.732 0.993 0.819 212455_at YTHDC1 4.91E−05 0.806 0.917 0.891 0.731 1.019 1.129 212543_at AIM1 3.20E−04 0.799 1.130 1.098 1.378 1.009 0.803 212658_at LHFPL2 3.59E−03 0.684 1.348 1.040 4.460 1.026 0.643 212663_at FKBP15 2.33E−03 0.755 1.119 1.090 1.355 1.049 0.771 212769_at TLE3 1.25E−03 0.737 0.811 0.719 0.406 1.080 1.501 212820_at DMXL2 1.05E−02 0.685 1.151 1.095 1.787 1.032 0.724 212997_s_at TLK2 2.57E−04 0.774 0.919 0.894 0.694 1.033 1.125 213218_at ZNF187 3.20E−03 0.728 0.857 0.789 0.574 1.029 1.288 213335_s_at ST3GAL6 7.83E−03 0.676 1.124 1.041 1.792 1.043 0.729 213459_at RPL37A 6.42E−03 0.699 0.848 0.759 0.440 1.056 1.415 213494_s_at YY1 9.76E−03 0.720 1.199 1.103 2.128 0.996 0.733 213877_x_at TCEB2 3.33E−04 0.761 0.912 0.913 0.738 1.045 1.135 214430_at GLA 1.89E−02 0.684 1.096 1.067 1.481 1.039 0.758 214511_x_at FCGR1B 7.32E−03 0.704 1.560 1.237 6.652 1.032 0.439 214629_x_at RTN4 6.28E−03 0.708 1.071 1.051 1.347 1.034 0.866 214683_s_at CLK1 6.36E−06 0.825 0.890 0.873 0.645 1.026 1.136 214820_at BRWD1 4.84E−02 0.661 0.909 0.867 0.602 1.024 1.386 214853_s_at SHC1 2.47E−05 0.834 1.131 1.112 1.327 1.003 0.788 214931_s_at SRPK2 6.51E−04 0.714 0.853 0.782 0.392 1.005 1.388 214953_s_at APP 1.43E−03 0.730 1.359 1.144 3.691 1.022 0.733 215049_x_at CD163 1.76E−02 0.689 1.279 1.144 2.654 1.060 0.596 215273_s_at TADA3L 4.12E−02 0.625 1.061 1.013 1.504 1.022 0.818 215293_s_at FRAG1 4.04E−03 0.733 0.882 0.817 0.610 1.012 1.344 215567_at FCF1 3.90E−03 0.735 0.863 0.815 0.378 1.058 1.285 215997_s_at CUL4B 3.73E−04 0.747 0.848 0.803 0.355 0.983 1.284 216484_x_at HDGF 3.37E−03 0.699 1.083 1.043 1.582 1.026 0.892 216950_s_at FCGR1A 1.44E−02 0.681 1.641 1.187 9.391 1.065 0.442 217383_at PGK1 8.49E−03 0.729 1.184 1.137 1.810 1.062 0.518 217769_s_at POMP 3.67E−03 0.694 1.090 1.028 1.439 1.046 0.882 217987_at ASNSD1 1.15E−03 0.700 0.810 0.739 0.247 1.051 1.331 218012_at TSPYL2 1.20E−02 0.658 0.894 0.855 0.505 1.059 1.261 218040_at PRPF38B 1.42E−02 0.676 0.936 0.928 0.608 1.045 1.100 218065_s_at TMEM9B 5.39E−04 0.760 1.114 1.085 1.302 1.036 0.823 218091_at HRB 7.79E−04 0.741 1.128 1.073 1.553 1.013 0.827 218127_at NFYB 3.48E−02 0.671 0.940 0.903 0.693 1.010 1.263 218143_s_at SCAMP2 5.41E−04 0.755 1.158 1.108 1.576 1.044 0.769 218206_x_at SCAND1 6.34E−03 0.704 1.077 1.025 1.378 1.019 0.811 218351_at COMMD8 6.25E−03 0.694 1.103 1.067 1.509 1.013 0.854 218499_at RP6-213H19.1 1.92E−02 0.654 0.934 0.889 0.696 1.034 1.182 218627_at DRAM 2.47E−02 0.646 1.183 1.044 3.160 1.054 0.756 218718_at PDGFC 1.61E−03 0.744 1.412 1.219 2.410 1.081 0.466 218732_at PTRH2 1.25E−03 0.764 1.165 1.121 1.504 1.006 0.677 218845_at DUSP22 1.91E−05 0.804 1.166 1.124 1.448 1.029 0.798 219316_s_at FLVCR2 1.34E−02 0.666 1.297 1.032 3.754 1.011 0.527 219358_s_at CENTA2 8.09E−03 0.701 1.234 1.074 2.542 1.023 0.671 219418_at NHEJ1 4.99E−03 0.734 1.130 1.077 1.640 1.025 0.776 219507_at RSRC1 2.97E−04 0.816 1.338 1.256 1.949 1.048 0.647 219826_at ZNF419 4.77E−02 0.646 0.869 0.786 0.498 1.069 1.621 219952_s_at MCOLN1 2.55E−02 0.688 1.155 1.050 1.709 0.993 0.714 220146_at TLR7 1.74E−03 0.734 1.404 1.258 3.269 1.066 0.524 220160_s_at KPTN 3.99E−03 0.713 1.151 1.064 2.178 1.044 0.806 220605_s_at SIRT2 3.64E−02 0.631 1.076 1.025 1.411 1.039 0.717 220750_s_at LEPRE1 3.60E−04 0.746 1.169 1.092 1.732 1.050 0.711 220865_s_at PDSS1 2.87E−02 0.663 1.182 1.072 2.102 1.072 0.669 220974_x_at SFXN3 3.54E−03 0.739 1.190 1.146 1.835 1.027 0.621 221428_s_at TBL1XR1 1.26E−02 0.681 0.892 0.851 0.591 1.023 1.348 221449_s_at ITFG1 1.23E−02 0.695 1.092 1.062 1.497 1.023 0.831 221580_s_at JOSD3 3.38E−02 0.669 0.930 0.916 0.678 1.041 1.244 221601_s_at FAIM3 3.66E−02 0.655 0.865 0.748 0.396 1.070 1.685 221647_s_at RIC8A 1.24E−03 0.740 1.093 1.070 1.354 0.997 0.884 221731_x_at VCAN 3.18E−02 0.681 1.129 1.063 1.633 1.027 0.613 221841_s_at KLF4 5.09E−04 0.784 1.403 1.237 2.790 1.017 0.456 221868_at PAIP2B 3.25E−03 0.789 0.823 0.752 0.480 1.030 1.665 221960_s_at RAB2A 1.66E−04 0.779 1.388 1.250 2.043 1.141 0.570 222217_s_at SLC27A3 1.31E−03 0.745 1.268 1.169 2.373 1.076 0.582 222231_s_at LRRC59 4.48E−04 0.775 1.135 1.083 1.692 1.027 0.848 222574_s_at DHX40 4.47E−04 0.778 0.867 0.834 0.581 1.008 1.592 222651_s_at TRPS1 3.06E−03 0.700 1.159 1.089 1.658 1.065 0.745 222670_s_at MAFB 3.79E−03 0.728 1.344 1.209 2.949 1.003 0.406 222700_at ARL6IP2 4.41E−03 0.713 0.906 0.882 0.557 1.035 1.228 222753_s_at SPCS3 2.08E−02 0.690 1.120 1.045 1.666 1.005 0.760 222774_s_at NETO2 8.14E−03 0.695 1.242 1.080 2.077 1.004 0.617 222980_at RAB10 2.51E−03 0.733 1.087 1.036 1.391 1.019 0.849 223064_at RNF181 3.87E−04 0.778 1.090 1.066 1.290 1.013 0.887 223158_s_at NEK6 2.79E−04 0.755 1.253 1.115 1.910 1.033 0.790 223444_at SENP7 9.71E−05 0.740 0.871 0.853 0.587 1.031 1.217 223465_at COL4A3BP 4.01E−02 0.638 1.133 1.049 1.730 1.067 0.690 223686_at TPK1 7.03E−03 0.724 0.898 0.859 0.561 1.031 1.277 223801_s_at APOL4 3.48E−02 0.611 1.094 1.035 2.338 1.046 0.681 223982_s_at PNPLA8 9.12E−04 0.739 0.922 0.907 0.631 1.011 1.115 224046_s_at PDE7A 9.29E−03 0.699 0.885 0.808 0.537 1.049 1.434 224387_at COMMD5 2.53E−02 0.696 1.139 1.088 1.866 1.021 0.557 224439_x_at RNF7 7.23E−05 0.808 1.175 1.145 1.488 1.035 0.766 224518_s_at ZNF559 1.43E−02 0.628 0.890 0.825 0.350 1.010 1.336 224726_at MIB1 2.04E−03 0.752 1.228 1.161 1.794 1.042 0.681 224818_at SORT1 1.43E−02 0.703 1.165 1.117 2.232 1.045 0.682 224917_at MIRN21 5.61E−03 0.697 1.158 1.078 1.651 1.046 0.727 224918_x_at MGST1 3.40E−02 0.691 1.253 1.068 3.299 0.991 0.606 224928_at SETD7 1.02E−03 0.766 1.195 1.148 1.825 1.059 0.666 225188_at RAPH1 1.64E−04 0.799 1.812 1.390 4.673 1.009 0.289 225341_at MTERFD3 4.65E−03 0.703 0.740 0.697 0.311 0.984 1.939 225365_at ZDHHC20 1.03E−02 0.699 1.118 1.091 1.694 1.045 0.821 225388_at TSPAN5 1.57E−02 0.649 0.865 0.841 0.454 1.004 1.505 225456_at MED1 3.15E−02 0.634 0.934 0.899 0.642 1.010 1.298 225844_at POLE4 1.74E−03 0.741 1.160 1.082 1.612 1.025 0.775 225870_s_at TRAPPC5 3.02E−02 0.671 1.117 1.055 1.616 1.027 0.783 226000_at CTTNBP2NL 1.61E−02 0.654 1.117 1.035 1.735 1.020 0.700 226042_at EDC3 7.20E−04 0.720 0.905 0.880 0.578 1.022 1.179 226059_at TOMM40L 3.81E−03 0.724 1.191 1.077 2.004 0.989 0.721 226115_at AHCTF1 4.40E−04 0.766 0.815 0.803 0.485 1.018 1.471 226127_at ALKBH3 2.12E−02 0.705 1.070 1.018 1.594 1.006 0.846 226220_at METTL9 6.02E−03 0.698 1.233 1.052 2.413 1.039 0.606 226323_at CCDC16 2.93E−03 0.726 0.908 0.897 0.707 1.024 1.266 226353_at SPPL2A 1.59E−03 0.741 1.122 1.076 1.689 0.990 0.846 226428_at TNPO2 1.36E−03 0.733 0.898 0.871 0.539 1.029 1.173 226459_at PIK3AP1 7.63E−03 0.668 1.159 1.059 2.046 1.027 0.759 226683_at SNAG1 1.05E−03 0.781 0.784 0.756 0.455 1.010 2.165 226763_at SESTD1 3.26E−04 0.765 1.324 1.190 2.717 1.134 0.687 227020_at YPEL2 6.11E−04 0.781 1.145 1.108 1.426 1.035 0.684 227149_at TNRC6C 5.77E−03 0.703 0.860 0.829 0.573 0.963 1.359 227173_s_at BACH2 1.04E−02 0.704 0.804 0.663 0.363 1.047 1.780 227558_at CBX4 3.84E−03 0.726 0.916 0.890 0.730 1.016 1.151 227560_at SFXN2 1.53E−02 0.710 0.910 0.872 0.661 1.020 1.282 227722_at RPS23 1.35E−03 0.696 0.655 0.412 0.037 1.013 2.284 227990_at SLU7 3.05E−04 0.725 0.895 0.859 0.604 1.012 1.142 228170_at OLIG1 1.54E−03 0.748 1.514 1.285 3.247 1.043 0.474 228176_at EDG3 6.68E−03 0.724 1.399 1.227 2.772 1.042 0.384 228234_at TICAM2 1.32E−02 0.698 1.149 1.093 1.711 1.023 0.753 228549_at TMEM63A 4.56E−02 0.650 0.893 0.790 0.476 1.044 1.432 228831_s_at GNG7 2.03E−02 0.648 0.842 0.815 0.345 1.045 1.693 229307_at ANKRD28 4.84E−03 0.689 1.410 1.147 3.169 1.165 0.460 229421_s_at FLJ20273 1.42E−02 0.703 1.213 1.097 2.394 1.057 0.669 229982_at QSER1 3.69E−05 0.799 1.379 1.175 2.491 1.007 0.700 230265_at SEL1L 2.15E−02 0.689 1.189 1.095 2.244 1.000 0.528 230480_at PIWIL4 8.24E−03 0.674 1.265 1.054 3.805 1.078 0.692 230837_at LOC647500 3.24E−03 0.704 0.901 0.839 0.632 1.000 1.329 230852_at STAC3 7.55E−03 0.710 1.152 1.095 2.110 1.063 0.782 230922_x_at FUNDC2 5.71E−03 0.723 0.906 0.881 0.564 1.012 1.245 231283_at MGAT4A 5.90E−03 0.713 0.873 0.801 0.559 1.040 1.323 231843_at DDX55 4.46E−04 0.768 0.874 0.842 0.389 1.038 1.203 231904_at U2AF1 2.03E−03 0.736 0.861 0.839 0.397 1.027 1.252 231914_at NUDT14 7.81E−03 0.681 1.085 1.038 1.845 1.039 0.800 232636_at SLITRK4 4.02E−04 0.766 1.492 1.337 3.430 1.066 0.414 232851_at FBXO3 2.72E−03 0.756 0.813 0.753 0.444 1.015 1.631 233169_at ZNF350 1.26E−03 0.713 0.849 0.795 0.412 1.000 1.347 234464_s_at EME1 9.59E−04 0.749 1.262 1.111 2.075 1.084 0.605 234733_s_at FANCM 1.56E−02 0.737 0.879 0.798 0.565 0.982 1.456 235024_at PHF17 2.63E−03 0.748 0.893 0.874 0.587 1.075 1.169 235067_at MKLN1 6.87E−04 0.741 0.872 0.848 0.437 1.030 1.170 235200_at ZNF561 1.60E−02 0.659 0.904 0.870 0.573 1.057 1.338 235359_at LRRC33 1.18E−03 0.754 1.232 1.124 2.131 1.061 0.544 235593_at ZEB2 3.53E−04 0.780 1.282 1.221 1.720 1.078 0.690 235623_at ELP2 6.41E−03 0.701 0.922 0.906 0.614 1.003 1.198 237504_at INTS10 1.65E−02 0.678 0.901 0.866 0.385 1.038 1.282 238429_at TMEM71 6.63E−04 0.745 0.847 0.840 0.535 1.007 1.358 238736_at REV3L 6.09E−03 0.692 0.880 0.839 0.589 1.036 1.477 238823_at FMNL3 7.45E−04 0.769 0.827 0.776 0.520 1.048 1.426 238909_at S100A10 8.25E−03 0.715 1.255 1.135 2.459 0.993 0.663 239897_at BCLAF1 1.82E−03 0.745 0.905 0.891 0.625 1.021 1.191 241368_at LSDP5 3.71E−02 0.674 0.860 0.744 0.562 0.959 1.743 241706_at CPNE8 2.46E−03 0.764 1.194 1.147 1.841 1.039 0.686 241731_x_at ZNF440 1.92E−02 0.672 0.919 0.864 0.597 1.014 1.250 242197_x_at CD36 8.67E−04 0.770 1.871 1.507 6.707 1.171 0.357 242561_at IPO9 2.50E−02 0.679 0.889 0.852 0.577 1.038 1.433 242569_at STAM2 4.84E−04 0.758 0.863 0.839 0.527 1.042 1.235 243982_at KLHL28 5.39E−03 0.695 0.870 0.841 0.435 1.060 1.304 244038_at WDR89 3.57E−02 0.688 0.897 0.833 0.585 1.020 1.498 244654_at MYO1G 1.31E−03 0.734 1.227 1.102 1.794 0.999 0.739 36566_at CTNS 1.24E−03 0.740 1.178 1.084 1.970 1.052 0.738 37549_g_at BBS9 2.83E−03 0.703 1.075 1.044 1.274 1.029 0.864 48659_at RP5-1077B9.4 1.97E−06 0.821 1.159 1.117 1.497 1.024 0.836 56829_at NIBP 1.20E−03 0.734 1.099 1.048 1.373 1.013 0.892 64486_at CORO1B 1.81E−04 0.782 1.210 1.119 1.964 1.019 0.736 65493_at HEATR6 4.99E−04 0.763 1.272 1.095 2.565 1.049 0.613 AFFX- GAPDH 4.88E−04 0.761 1.103 1.059 1.456 1.027 0.868 HUMGAPDH/M33197_3_at

TABLE 4 Extreme NYHA Extreme Average III-IV- Control- fold- directional directional Statistical Maximum change fold-change fold-change significance overall gene Average observed Average observed of accuracy of expression fold-change (Extreme fold-change (Extreme differential classification (NYHA expression at NYHA expression at Control/ Affymetrix Probe expression power III-IV/ sensitivity = III-IV/average specificity = average set ID Gene symbol (p-value) (ROC AUC) Control) 0.6 Control) 0.6 Control) 1552318_at GIMAP1 1.63E−02 0.527 0.855 0.945 0.543 1.053 1.534 1552630_a_at SRCAP 9.37E−04 0.687 0.815 0.804 0.431 1.032 1.417 1554149_at CLDND1 1.04E−03 0.672 0.856 0.841 0.558 1.048 1.291 1554539_a_at RHOF 5.37E−03 0.536 0.825 0.860 0.317 1.029 1.373 1554606_at CCDC100 1.41E−05 0.701 0.760 0.811 0.397 1.100 1.175 1555630_a_at RAB34 1.50E−03 0.727 1.306 1.108 2.425 1.046 0.591 1555963_x_at B3GNT7 6.37E−04 0.693 1.386 1.113 5.102 1.105 0.719 1555996_s_at EIF4A2 1.18E−03 0.584 0.794 0.822 0.322 1.100 1.421 1556113_at DKFZp451A211 3.55E−03 0.692 1.131 1.070 1.530 1.060 0.722 1556283_s_at FGFR1OP2 1.60E−03 0.720 1.237 1.103 1.751 1.028 0.634 1556864_at TECT1 1.98E−03 0.724 0.852 0.866 0.496 1.010 1.424 1557066_at LUC7L 3.12E−04 0.689 0.776 0.844 0.329 1.064 1.349 1558277_at ZNF740 4.88E−02 0.737 1.175 1.122 2.035 1.038 0.648 1558755_x_at ZNF763 1.20E−04 0.697 0.753 0.767 0.413 1.118 1.312 1561146_at VPS35 1.02E−03 0.732 0.790 0.771 0.442 1.030 1.929 1564962_at ZNF92 1.90E−05 0.793 0.748 0.734 0.511 1.027 1.521 1567013_at NFE2L2 8.33E−03 0.564 1.169 0.891 1.897 0.958 0.846 1568815_a_at DDX50 5.34E−04 0.687 0.762 0.811 0.345 1.010 2.085 200010_at RPL11 4.31E−03 0.569 0.902 0.993 0.594 1.022 1.220 200059_s_at RHOA 2.79E−04 0.730 1.068 1.036 1.212 1.015 0.867 200091_s_at RPS25 8.54E−04 0.562 0.881 0.920 0.629 1.018 1.294 200650_s_at LDHA 1.50E−03 0.635 1.136 1.030 1.464 1.051 0.736 200672_x_at SPTBN1 7.47E−05 0.649 0.773 0.796 0.325 1.030 1.532 200677_at PTTG1IP 9.05E−04 0.597 1.135 1.010 1.526 1.034 0.747 200713_s_at MAPRE1 5.99E−03 0.767 1.073 1.066 1.514 1.009 0.906 200822_x_at TPI1 5.74E−05 0.701 1.162 1.063 1.629 1.009 0.723 200829_x_at ZNF207 1.09E−03 0.769 1.125 1.082 1.606 1.042 0.812 200839_s_at CTSB 2.90E−05 0.727 1.330 1.117 2.297 1.034 0.546 200932_s_at DCTN2 2.37E−03 0.712 1.088 1.033 1.558 1.024 0.881 200950_at ARPC1A 8.34E−05 0.739 1.148 1.067 1.573 1.009 0.880 201031_s_at HNRPH1 1.24E−03 0.539 0.859 0.940 0.549 1.068 1.235 201075_s_at SMARCC1 3.51E−05 0.797 0.864 0.839 0.665 1.024 1.246 201098_at COPB2 1.31E−04 0.739 1.095 1.039 1.369 1.020 0.897 201105_at LGALS1 2.12E−03 0.778 1.345 1.255 2.736 1.039 0.513 201172_x_at ATP6V0E1 1.67E−04 0.681 1.113 1.042 1.441 1.030 0.865 201186_at LRPAP1 3.57E−04 0.649 1.200 1.026 1.904 1.027 0.783 201193_at IDH1 6.48E−07 0.738 1.310 1.119 2.191 1.078 0.784 201198_s_at PSMD1 7.45E−03 0.771 1.114 1.124 1.447 1.053 0.736 201220_x_at CTBP2 1.14E−04 0.646 1.160 1.036 1.406 1.028 0.796 201234_at ILK 1.18E−05 0.773 1.194 1.071 1.858 1.015 0.867 201357_s_at SF3A1 7.81E−03 0.814 0.898 0.826 0.611 1.002 1.293 201363_s_at IVNS1ABP 4.11E−04 0.762 0.856 0.852 0.590 1.016 1.300 201400_at PSMB3 8.05E−05 0.695 1.205 1.044 2.162 1.011 0.820 201421_s_at WDR77 1.97E−02 0.503 0.894 0.945 0.592 1.060 1.260 201422_at IFI30 1.41E−05 0.712 1.234 1.086 1.962 1.029 0.686 201426_s_at VIM 7.11E−04 0.753 1.123 1.052 1.406 1.004 0.847 201453_x_at RHEB 4.11E−04 0.726 1.101 1.055 1.424 1.025 0.810 201470_at GSTO1 8.72E−04 0.734 1.218 1.076 2.377 1.004 0.770 201478_s_at DKC1 2.09E−04 0.605 0.861 0.903 0.534 1.039 1.208 201527_at ATP6V1F 2.23E−03 0.699 1.110 1.057 1.612 1.034 0.839 201536_at DUSP3 2.12E−05 0.626 1.303 1.024 2.512 1.032 0.742 201554_x_at GYG1 8.98E−04 0.615 1.307 0.976 3.876 1.010 0.674 201556_s_at VAMP2 1.49E−04 0.759 0.801 0.758 0.589 0.985 1.523 201576_s_at GLB1 1.94E−04 0.707 1.197 1.048 2.099 1.022 0.743 201590_x_at ANXA2 1.08E−04 0.799 1.281 1.151 2.012 1.062 0.631 201628_s_at RRAGA 6.66E−04 0.732 1.104 1.043 1.444 1.029 0.842 201788_at DDX42 6.53E−05 0.629 0.867 0.890 0.661 1.018 1.256 201900_s_at AKR1A1 4.38E−03 0.723 1.170 1.063 2.155 1.023 0.770 202068_s_at LDLR 2.42E−05 0.703 1.689 1.125 4.236 1.029 0.406 202104_s_at SPG7 2.82E−04 0.598 0.834 0.872 0.420 1.066 1.174 202185_at PLOD3 1.70E−02 0.770 1.101 1.102 1.565 1.023 0.797 202192_s_at GAS7 2.75E−03 0.601 1.243 0.974 1.773 1.000 0.641 202201_at BLVRB 1.74E−04 0.720 1.335 1.066 2.830 1.001 0.675 202249_s_at WDR42A 4.50E−04 0.697 0.890 0.871 0.627 1.034 1.224 202252_at RAB13 7.48E−05 0.685 1.393 1.109 3.759 1.083 0.711 202262_x_at DDAH2 1.69E−03 0.501 1.234 0.909 1.835 0.992 0.779 202380_s_at NKTR 1.92E−04 0.514 0.827 0.916 0.437 1.066 1.314 202381_at ADAM9 5.40E−05 0.582 1.376 0.967 2.456 0.988 0.667 202428_x_at DBI 9.95E−03 0.806 1.118 1.121 2.014 1.038 0.807 202461_at EIF2B2 4.07E−02 0.795 1.117 1.147 1.714 1.059 0.653 202522_at PITPNB 2.98E−02 0.752 1.063 1.066 1.239 1.017 0.822 202523_s_at SPOCK2 3.70E−05 0.672 0.674 0.614 0.239 1.076 1.476 202594_at LEPROTL1 8.21E−04 0.553 0.883 0.920 0.620 1.048 1.194 202623_at EAPP 1.38E−05 0.770 0.896 0.900 0.709 1.012 1.174 202652_at APBB1 4.37E−05 0.719 0.753 0.789 0.243 1.016 1.429 202724_s_at FOXO1 8.60E−04 0.659 0.847 0.860 0.468 0.994 1.437 202750_s_at TFIP11 4.59E−03 0.609 1.158 1.002 1.504 1.094 0.532 202778_s_at ZMYM2 6.31E−04 0.733 0.899 0.873 0.660 1.026 1.162 202910_s_at CD97 1.12E−03 0.526 1.208 0.955 1.720 1.038 0.619 202928_s_at PHF1 1.91E−05 0.772 0.818 0.797 0.523 1.011 1.320 202944_at NAGA 7.63E−04 0.731 1.219 1.130 1.669 1.008 0.676 202979_s_at CREBZF 2.80E−03 0.559 0.834 0.905 0.499 1.061 1.414 203003_at MEF2D 2.66E−02 0.809 0.897 0.808 0.619 0.978 1.416 203127_s_at SPTLC2 6.30E−04 0.721 1.247 1.118 2.496 1.058 0.719 203137_at WTAP 2.24E−04 0.695 0.889 0.895 0.679 1.030 1.177 203184_at FBN2 1.61E−03 0.545 1.573 0.878 3.839 1.051 0.405 203234_at UPP1 3.76E−04 0.680 1.317 1.062 2.790 1.007 0.567 203278_s_at PHF21A 4.88E−03 0.509 1.204 0.923 2.629 1.056 0.730 203305_at F13A1 1.01E−04 0.649 1.505 1.057 3.284 1.052 0.534 203371_s_at NDUFB3 4.53E−04 0.562 1.224 0.961 2.021 1.047 0.795 203413_at NELL2 4.76E−05 0.688 0.608 0.659 0.085 1.017 1.764 203416_at CD53 4.04E−04 0.680 1.085 1.035 1.272 1.019 0.867 203492_x_at CEP57 1.48E−03 0.559 0.863 0.895 0.564 1.012 1.316 203534_at LSM1 4.10E−04 0.812 1.147 1.111 1.682 1.024 0.815 203535_at S100A9 1.10E−03 0.631 1.089 1.018 1.318 1.024 0.830 203578_s_at SLC7A6 6.44E−04 0.564 0.776 0.822 0.380 0.984 1.600 203748_x_at RBMS1 1.84E−03 0.555 1.106 0.990 1.529 0.996 0.807 203844_at VHL 8.32E−04 0.672 1.099 1.026 1.551 1.029 0.794 203880_at COX17 7.60E−03 0.739 1.136 1.089 1.912 1.045 0.695 203912_s_at DNASE1L1 9.10E−04 0.754 1.221 1.149 1.786 1.051 0.647 203939_at NT5E 7.33E−04 0.703 0.743 0.632 0.374 1.004 1.778 203971_at SLC31A1 6.87E−04 0.597 1.200 1.035 1.622 1.076 0.644 204050_s_at CLTA 2.98E−03 0.753 1.108 1.049 1.475 1.010 0.865 204068_at STK3 5.62E−03 0.526 1.303 0.852 2.631 1.130 0.600 204099_at SMARCD3 7.02E−06 0.674 1.463 1.066 2.956 1.074 0.701 204143_s_at ENOSF1 1.77E−03 0.512 0.718 0.885 0.274 0.954 1.941 204204_at SLC31A2 2.07E−03 0.559 1.255 0.942 1.817 1.081 0.501 204214_s_at RAB32 1.76E−04 0.610 1.245 1.003 2.378 0.997 0.829 204232_at FCER1G 6.03E−04 0.601 1.262 1.003 1.996 1.111 0.642 204243_at RLF 7.04E−05 0.703 1.243 1.087 1.700 1.065 0.752 204249_s_at LMO2 8.74E−05 0.739 1.210 1.127 1.639 1.014 0.804 204291_at ZNF518 5.29E−04 0.632 0.872 0.902 0.624 1.037 1.201 204342_at SLC25A24 4.51E−04 0.593 1.186 0.977 1.794 0.996 0.769 204352_at TRAF5 1.04E−03 0.564 0.728 0.848 0.200 1.034 1.955 204401_at KCNN4 2.66E−03 0.695 0.813 0.732 0.413 1.040 1.629 204504_s_at HIRIP3 1.20E−03 0.645 0.887 0.914 0.654 1.035 1.196 204617_s_at ACD 2.14E−03 0.703 0.871 0.875 0.355 1.045 1.209 204645_at CCNT2 2.13E−05 0.747 0.863 0.867 0.644 1.009 1.238 204675_at SRD5A1 6.23E−04 0.799 1.369 1.170 2.230 1.033 0.572 204689_at HHEX 8.76E−04 0.600 1.147 0.986 1.531 1.045 0.767 204801_s_at DHRS12 4.89E−03 0.757 0.782 0.614 0.336 1.077 1.834 205235_s_at MPHOSPH1 3.08E−04 0.737 0.883 0.886 0.774 1.033 1.309 205254_x_at TCF7 9.88E−05 0.649 0.666 0.670 0.118 1.007 1.924 205256_at ZBTB39 8.23E−04 0.672 0.887 0.890 0.659 1.012 1.321 205322_s_at MTF1 2.76E−04 0.598 1.175 0.989 1.704 1.013 0.794 205340_at ZBTB24 1.61E−03 0.504 0.851 0.948 0.524 1.043 1.294 205349_at GNA15 3.35E−04 0.589 1.215 1.016 1.697 1.037 0.733 205550_s_at BRE 2.80E−04 0.662 1.101 1.023 1.277 1.023 0.835 205811_at POLG2 2.41E−03 0.535 0.871 0.985 0.558 1.040 1.242 205835_s_at YTHDC2 3.15E−03 0.586 0.786 0.884 0.410 1.059 1.395 205895_s_at NOLC1 6.77E−04 0.623 0.787 0.843 0.296 1.041 1.369 205965_at BATF 6.51E−04 0.659 1.220 1.032 1.743 1.013 0.796 205976_at FASTKD2 9.60E−04 0.617 0.724 0.821 0.197 1.110 1.504 206015_s_at FOXJ3 5.61E−04 0.571 0.907 0.942 0.707 1.029 1.155 206037_at CCBL1 2.95E−03 0.613 0.885 0.909 0.657 1.028 1.272 206170_at ADRB2 2.47E−03 0.772 1.320 1.285 2.017 1.109 0.361 206182_at ZNF134 2.21E−04 0.657 0.853 0.878 0.551 1.026 1.305 206343_s_at NRG1 5.42E−04 0.630 2.271 0.960 6.376 0.930 0.314 206542_s_at SMARCA2 1.70E−04 0.732 0.873 0.867 0.656 1.017 1.228 206580_s_at EFEMP2 1.51E−03 0.533 1.175 0.984 1.684 1.008 0.754 206715_at TFEC 4.89E−04 0.662 1.400 1.088 4.246 1.068 0.516 206834_at HBD 6.69E−04 0.614 2.762 0.983 16.461 1.002 0.396 206968_s_at NFRKB 3.96E−04 0.633 0.850 0.926 0.443 1.028 1.276 207075_at NLRP3 4.83E−04 0.578 1.407 0.993 2.969 1.035 0.659 207078_at MED6 2.91E−05 0.662 0.797 0.847 0.400 1.048 1.304 207113_s_at TNF 8.71E−04 0.691 1.277 1.120 1.866 1.123 0.644 207164_s_at ZNF238 1.12E−02 0.714 0.870 0.772 0.266 1.012 1.390 207233_s_at MITF 5.10E−04 0.569 1.252 0.934 2.368 0.975 0.802 207416_s_at NFATC3 7.25E−04 0.607 0.858 0.885 0.413 1.031 1.207 207513_s_at ZNF189 3.50E−03 0.684 0.897 0.883 0.624 1.023 1.332 207543_s_at P4HA1 2.41E−04 0.653 1.239 1.041 1.714 0.985 0.746 207564_x_at OGT 1.99E−04 0.646 0.801 0.851 0.521 1.053 1.345 207971_s_at CEP68 3.91E−04 0.541 0.784 0.869 0.470 0.998 1.927 208121_s_at PTPRO 4.03E−05 0.772 1.561 1.319 2.929 1.136 0.562 208161_s_at ABCC3 2.38E−04 0.793 1.654 1.190 4.098 1.067 0.473 208269_s_at ADAM28 5.81E−04 0.747 0.840 0.819 0.521 1.052 1.412 208309_s_at MALT1 4.29E−02 0.504 0.853 0.942 0.564 1.108 1.460 208527_x_at HIST1H2BE 1.49E−03 0.554 1.235 0.890 1.932 1.029 0.724 208579_x_at H2BFS 4.68E−04 0.546 1.315 0.936 2.258 1.024 0.723 208635_x_at NACA 1.35E−02 0.567 0.921 1.011 0.618 1.062 1.149 208659_at CLIC1 1.22E−04 0.664 1.129 1.026 1.682 0.987 0.890 208680_at PRDX1 1.84E−03 0.744 1.215 1.128 2.149 1.067 0.676 208749_x_at FLOT1 1.60E−02 0.564 1.170 0.878 2.242 1.032 0.693 208771_s_at LTA4H 1.62E−04 0.682 1.322 1.108 2.296 1.057 0.567 208780_x_at VAPA 2.75E−03 0.631 1.173 0.993 1.827 0.989 0.728 208798_x_at GOLGA8A 4.40E−04 0.539 0.706 0.797 0.221 1.041 1.693 208805_at PSMA6 1.15E−02 0.725 1.120 1.048 2.143 1.028 0.808 208903_at RPS28 6.94E−04 0.604 0.830 0.889 0.283 1.009 1.373 208921_s_at SRI 1.31E−03 0.743 1.115 1.082 1.434 1.028 0.806 208923_at CYFIP1 7.20E−06 0.724 1.343 1.112 2.294 1.077 0.697 208946_s_at BECN1 5.04E−04 0.768 0.935 0.922 0.724 1.012 1.115 208962_s_at FADS1 1.10E−03 0.622 1.387 0.961 2.687 1.011 0.572 209040_s_at PSMB8 4.28E−03 0.755 1.115 1.071 1.671 1.018 0.853 209067_s_at HNRPDL 5.68E−04 0.586 0.810 0.848 0.474 1.060 1.358 209072_at MBP 3.35E−04 0.635 1.610 1.082 4.703 1.071 0.564 209099_x_at JAG1 1.15E−06 0.649 1.437 1.018 2.677 1.033 0.692 209124_at MYD88 2.46E−04 0.657 1.117 1.066 1.346 0.999 0.882 209180_at RABGGTB 3.48E−03 0.520 0.857 0.958 0.478 1.063 1.322 209191_at TUBB6 7.44E−04 0.625 1.407 0.932 3.209 1.061 0.615 209212_s_at KLF5 1.87E−05 0.517 1.233 0.992 1.998 1.035 0.708 209218_at SQLE 1.66E−03 0.701 1.403 1.124 3.611 1.085 0.578 209236_at SLC23A2 5.20E−06 0.661 0.826 0.867 0.454 1.040 1.181 209251_x_at TUBA1C 2.59E−04 0.662 1.147 1.042 1.461 1.045 0.809 209259_s_at SMC3 1.80E−03 0.558 0.883 0.939 0.554 1.064 1.172 209269_s_at SYK 3.93E−02 0.736 0.893 0.787 0.600 1.055 1.675 209330_s_at HNRPD 1.01E−03 0.638 0.811 0.857 0.355 1.012 1.467 209339_at SIAH2 4.35E−04 0.617 1.163 1.037 1.704 1.056 0.788 209430_at BTAF1 9.75E−04 0.636 0.870 0.871 0.595 1.032 1.263 209675_s_at HNRPUL1 1.35E−04 0.744 0.843 0.856 0.585 1.036 1.341 209684_at RIN2 2.80E−04 0.676 1.382 0.998 2.641 1.004 0.558 209806_at HIST1H2BK 5.51E−06 0.567 1.391 0.934 2.388 1.046 0.743 209840_s_at LRRN3 7.84E−04 0.581 0.326 0.197 0.031 0.711 7.962 209870_s_at APBA2 2.53E−03 0.592 0.811 0.804 0.444 1.050 1.662 209892_at FUT4 3.70E−05 0.736 1.270 1.114 1.952 1.052 0.714 209906_at C3AR1 2.19E−04 0.616 1.553 0.969 3.408 1.031 0.589 210061_at ZNF589 1.27E−03 0.594 0.797 0.865 0.461 1.077 1.339 210145_at PLA2G4A 4.81E−05 0.736 1.507 1.194 3.513 1.133 0.674 210156_s_at PCMT1 2.36E−03 0.697 1.113 1.076 1.396 1.058 0.835 210166_at TLR5 2.85E−03 0.503 1.372 0.855 3.509 0.945 0.538 210434_x_at JTB 2.30E−04 0.776 1.106 1.060 1.320 1.044 0.845 210644_s_at LAIR1 1.35E−04 0.782 1.278 1.169 2.510 1.031 0.696 210648_x_at SNX3 1.68E−05 0.755 1.165 1.076 1.565 1.002 0.854 210875_s_at ZEB1 1.97E−04 0.774 0.783 0.744 0.380 1.005 1.535 211047_x_at AP2S1 6.86E−04 0.782 1.149 1.113 1.594 1.022 0.779 211058_x_at TUBA1B 1.37E−03 0.666 1.095 1.026 1.440 1.019 0.857 211185_s_at SF3B1 9.79E−05 0.722 0.918 0.934 0.779 1.025 1.150 211272_s_at DGKA 3.03E−04 0.600 0.744 0.797 0.312 0.993 1.724 211323_s_at ITPR1 6.83E−05 0.657 0.798 0.823 0.439 1.063 1.345 211383_s_at WDR37 4.56E−02 0.741 1.065 1.072 1.305 1.055 0.826 211429_s_at SERPINA1 6.77E−04 0.516 1.121 0.975 1.461 1.019 0.855 211506_s_at IL8 1.20E−02 0.799 0.710 0.273 0.050 1.059 2.135 211546_x_at SNCA 1.62E−03 0.507 1.175 0.948 2.044 1.016 0.733 211684_s_at DYNC1I2 1.98E−03 0.746 1.186 1.114 2.083 1.047 0.655 211729_x_at BLVRA 2.80E−03 0.717 1.241 1.067 2.744 1.041 0.607 211856_x_at CD28 1.53E−04 0.693 0.654 0.666 0.115 1.099 1.625 211946_s_at BAT2D1 4.37E−04 0.659 0.910 0.891 0.670 1.039 1.095 212030_at RBM25 8.72E−07 0.697 0.818 0.884 0.630 1.012 1.292 212042_x_at hCG_31916///RPL7 5.64E−04 0.555 0.896 0.960 0.621 1.041 1.132 212132_at LSM14A 1.98E−05 0.699 0.881 0.896 0.576 1.017 1.224 212331_at RBL2 8.39E−05 0.669 0.871 0.892 0.634 1.018 1.199 212334_at GNS 1.44E−03 0.707 1.152 1.065 1.462 0.993 0.819 212406_s_at PCMTD2 6.55E−03 0.568 0.864 0.949 0.526 1.067 1.217 212455_at YTHDC1 3.94E−08 0.799 0.878 0.893 0.741 1.019 1.129 212543_at AIM1 9.82E−03 0.808 1.090 1.101 1.248 1.009 0.803 212658_at LHFPL2 8.19E−06 0.681 1.569 1.033 6.125 1.026 0.643 212663_at FKBP15 1.17E−04 0.749 1.147 1.087 1.514 1.049 0.771 212820_at DMXL2 1.16E−04 0.686 1.249 1.092 2.031 1.032 0.724 212932_at RAB3GAP1 3.29E−03 0.553 0.877 0.930 0.639 1.035 1.268 212989_at SGMS1 4.86E−03 0.551 1.173 0.904 2.079 1.010 0.824 212997_s_at TLK2 1.18E−04 0.764 0.915 0.893 0.789 1.033 1.125 213021_at GOSR1 8.87E−05 0.606 0.889 0.940 0.705 1.040 1.139 213152_s_at SFRS2B 1.12E−03 0.581 0.797 0.857 0.365 1.038 1.494 213205_s_at RAD54L2 4.99E−04 0.634 0.839 0.890 0.515 1.035 1.227 213218_at ZNF187 2.35E−04 0.714 0.816 0.805 0.447 1.029 1.288 213266_at 76P 7.22E−03 0.507 0.864 0.922 0.574 1.066 1.295 213302_at PFAS 6.03E−04 0.641 0.744 0.798 0.301 1.017 1.738 213335_s_at ST3GAL6 1.69E−03 0.679 1.186 1.040 1.995 1.043 0.729 213397_x_at RNASE4 3.28E−04 0.611 1.485 1.023 3.133 1.066 0.474 213459_at RPL37A 2.70E−03 0.711 0.822 0.732 0.275 1.056 1.415 213494_s_at YY1 6.88E−04 0.711 1.279 1.077 2.064 0.996 0.733 213540_at HSD17B8 1.25E−04 0.636 0.838 0.828 0.544 1.033 1.262 213693_s_at MUC1 2.02E−04 0.520 1.074 0.995 1.390 1.004 0.922 213827_at SNX26 1.09E−03 0.600 0.848 0.886 0.536 1.044 1.276 213877_x_at TCEB2 3.61E−03 0.770 0.930 0.912 0.772 1.045 1.135 214045_at LIAS 8.31E−03 0.591 0.817 1.010 0.438 1.068 1.464 214057_at MCL1 2.95E−04 0.638 1.229 1.019 1.921 1.016 0.734 214330_at ATPAF2 1.30E−03 0.611 0.815 0.856 0.543 1.001 1.429 214364_at MTERFD2 1.40E−03 0.576 0.776 0.856 0.427 1.006 1.517 214430_at GLA 7.00E−04 0.672 1.180 1.057 1.596 1.039 0.758 214511_x_at FCGR1B 2.32E−04 0.686 1.889 1.114 5.029 1.032 0.439 214629_x_at RTN4 3.15E−05 0.700 1.125 1.037 1.414 1.034 0.866 214683_s_at CLK1 4.57E−05 0.822 0.905 0.872 0.671 1.026 1.136 214820_at BRWD1 8.03E−04 0.655 0.837 0.862 0.447 1.024 1.386 214853_s_at SHC1 4.92E−04 0.835 1.124 1.110 1.462 1.005 0.788 214931_s_at SRPK2 6.41E−03 0.709 0.882 0.782 0.392 1.005 1.388 214953_s_at APP 3.46E−04 0.711 1.315 1.121 2.271 1.022 0.733 215009_s_at SEC31A 2.97E−04 0.674 0.804 0.875 0.419 1.104 1.227 215049_x_at CD163 1.03E−04 0.673 1.485 1.101 3.452 1.060 0.596 215273_s_at TADA3L 3.62E−04 0.600 1.113 1.005 1.363 1.022 0.818 215293_s_at FRAG1 1.44E−03 0.712 0.864 0.828 0.571 1.012 1.344 215567_at FCF1 6.02E−06 0.720 0.766 0.838 0.427 1.058 1.285 215997_s_at CUL4B 2.27E−02 0.751 0.902 0.801 0.381 0.982 1.284 216484_x_at HDGF 1.51E−03 0.686 1.098 1.036 1.414 1.026 0.892 216950_s_at FCGR1A 3.05E−04 0.665 1.987 1.063 6.196 1.065 0.442 217383_at PGK1 1.19E−03 0.724 1.286 1.134 2.091 1.066 0.518 217403_s_at ZNF227 1.04E−03 0.589 0.838 0.909 0.471 1.024 1.371 217466_x_at LOC400963///LOC440 3.06E−04 0.593 0.857 0.915 0.512 1.054 1.225 217769_s_at POMP 3.29E−03 0.672 1.107 1.008 2.036 1.046 0.882 217778_at SLC39A1 3.19E−03 0.573 1.148 0.992 1.544 1.038 0.792 217824_at UBE2J1 1.15E−04 0.604 1.266 1.011 1.979 1.061 0.748 217987_at ASNSD1 2.23E−04 0.720 0.774 0.729 0.286 1.051 1.331 217995_at SQRDL 6.59E−04 0.627 1.191 1.028 1.859 1.028 0.662 218012_at TSPYL2 9.33E−06 0.631 0.792 0.869 0.350 1.059 1.261 218040_at PRPF38B 2.17E−04 0.672 0.898 0.930 0.627 1.046 1.100 218091_at HRB 2.64E−05 0.741 1.206 1.070 1.892 1.013 0.827 218125_s_at CCDC25 5.15E−03 0.533 0.899 0.949 0.613 0.982 1.359 218127_at NFYB 9.61E−05 0.652 0.872 0.904 0.553 1.010 1.263 218143_s_at SCAMP2 8.06E−03 0.758 1.111 1.104 1.394 1.044 0.769 218206_x_at SCAND1 3.87E−03 0.706 1.126 1.024 1.943 1.019 0.811 218289_s_at UBE1DC1 1.10E−03 0.599 0.824 0.874 0.325 1.057 1.347 218325_s_at DIDO1 2.92E−02 0.603 0.926 0.982 0.610 1.001 1.365 218351_at COMMD8 1.68E−03 0.678 1.119 1.049 1.495 1.013 0.854 218499_at RP6-213H19.1 4.03E−05 0.638 0.878 0.894 0.701 1.034 1.182 218627_at DRAM 1.60E−05 0.627 1.344 1.000 2.197 1.054 0.756 218718_at PDGFC 1.59E−02 0.733 1.416 1.164 3.042 1.081 0.466 218732_at PTRH2 1.13E−04 0.761 1.222 1.114 1.725 1.010 0.677 218845_at DUSP22 1.01E−05 0.788 1.174 1.109 1.496 1.029 0.798 218962_s_at TMEM168 1.38E−03 0.584 0.876 0.913 0.674 1.046 1.245 219130_at CCDC76 7.95E−04 0.512 0.828 0.909 0.465 1.083 1.278 219316_s_at FLVCR2 4.82E−04 0.666 1.382 1.020 3.266 1.009 0.527 219343_at CDC37L1 1.63E−03 0.591 0.864 0.907 0.581 1.061 1.211 219358_s_at CENTA2 4.62E−04 0.707 1.294 1.079 2.293 1.020 0.671 219507_at RSRC1 1.27E−02 0.819 1.214 1.261 1.890 1.048 0.647 219765_at ZNF329 7.47E−05 0.622 0.724 0.826 0.342 1.033 1.718 219787_s_at ECT2 3.84E−05 0.578 1.433 0.943 3.396 0.983 0.635 219822_at MTRF1 1.07E−03 0.542 0.866 0.911 0.582 1.022 1.328 219826_at ZNF419 7.33E−05 0.636 0.733 0.790 0.407 1.069 1.621 219952_s_at MCOLN1 8.19E−04 0.671 1.252 1.022 1.800 0.993 0.714 220044_x_at CROP 1.66E−02 0.547 0.889 0.945 0.631 1.086 1.212 220146_at TLR7 1.45E−04 0.739 1.417 1.258 3.271 1.066 0.524 220160_s_at KPTN 4.43E−04 0.726 1.194 1.065 2.166 1.043 0.806 220386_s_at EML4 6.48E−04 0.533 0.828 0.930 0.439 1.048 1.453 220578_at ADAMTSL4 9.20E−04 0.664 1.247 1.013 2.047 1.000 0.792 220605_s_at SIRT2 6.43E−04 0.605 1.127 1.009 1.564 1.039 0.717 220610_s_at LRRFIP2 6.71E−04 0.591 1.174 1.001 2.047 1.035 0.853 220690_s_at DHRS7B 1.43E−03 0.513 1.150 0.991 1.641 1.056 0.778 220750_s_at LEPRE1 3.62E−03 0.747 1.135 1.089 1.639 1.050 0.711 220865_s_at PDSS1 1.58E−05 0.638 1.357 1.049 3.061 1.072 0.669 220974_x_at SFXN3 1.87E−03 0.726 1.210 1.143 1.550 1.027 0.621 221011_s_at LBH 1.00E−03 0.543 0.767 0.861 0.247 1.052 1.644 221206_at PMS2 1.26E−03 0.606 0.854 0.924 0.627 1.044 1.338 221264_s_at TARDBP 1.11E−02 0.505 0.832 0.946 0.578 1.066 1.576 221428_s_at TBL1XR1 7.90E−04 0.667 0.851 0.854 0.571 1.023 1.348 221449_s_at ITFG1 7.63E−04 0.684 1.155 1.049 1.919 1.023 0.831 221580_s_at JOSD3 5.70E−05 0.655 0.859 0.920 0.697 1.041 1.244 221601_s_at FAIM3 5.94E−05 0.639 0.703 0.753 0.249 1.070 1.685 221647_s_at RIC8A 1.51E−03 0.723 1.097 1.060 1.386 0.997 0.884 221731_x_at VCAN 6.55E−05 0.684 1.267 1.067 1.761 1.028 0.613 221757_at PIK3IP1 1.49E−04 0.625 0.761 0.818 0.377 1.004 1.612 221841_s_at KLF4 4.89E−05 0.781 1.476 1.217 2.292 1.016 0.456 221868_at PAIP2B 1.37E−04 0.776 0.764 0.750 0.419 1.029 1.665 221960_s_at RAB2A 2.55E−05 0.765 1.490 1.200 2.502 1.141 0.570 222217_s_at SLC27A3 3.36E−04 0.736 1.314 1.162 2.731 1.078 0.582 222231_s_at LRRC59 8.10E−04 0.761 1.150 1.073 1.672 1.027 0.848 222574_s_at DHX40 9.62E−04 0.782 0.871 0.832 0.480 1.008 1.592 222605_at RCOR3 6.53E−04 0.650 0.898 0.940 0.707 1.029 1.153 222651_s_at TRPS1 1.37E−05 0.701 1.249 1.091 1.798 1.063 0.745 222670_s_at MAFB 1.51E−03 0.723 1.369 1.190 2.682 1.003 0.406 222688_at PHCA 1.11E−03 0.645 1.236 1.054 1.927 1.053 0.596 222700_at ARL6IP2 9.52E−06 0.701 0.850 0.885 0.593 1.035 1.228 222753_s_at SPCS3 3.94E−04 0.670 1.206 1.039 1.695 1.005 0.760 222757_s_at ZAK 3.06E−04 0.555 1.363 0.948 2.518 1.016 0.546 222774_s_at NETO2 9.82E−04 0.680 1.297 1.051 2.424 1.004 0.617 222884_at ZNF346 1.52E−03 0.563 0.894 0.951 0.703 1.050 1.245 222980_at RAB10 3.81E−04 0.716 1.107 1.029 1.458 1.019 0.849 222982_x_at SLC38A2 5.48E−04 0.526 1.108 0.956 1.345 1.039 0.884 223023_at BET1L 1.11E−02 0.523 0.886 0.965 0.615 1.013 1.456 223064_at RNF181 6.20E−04 0.773 1.109 1.066 1.607 1.013 0.887 223158_s_at NEK6 7.23E−05 0.765 1.254 1.150 1.742 1.032 0.790 223380_s_at LATS2 2.25E−03 0.563 1.236 0.973 1.969 1.023 0.668 223444_at SENP7 9.07E−05 0.720 0.882 0.868 0.616 1.031 1.217 223465_at COL4A3BP 4.36E−04 0.611 1.234 1.023 1.827 1.067 0.690 223590_at ZNF700 2.30E−04 0.576 0.859 0.920 0.643 1.012 1.304 223801_s_at APOL4 1.56E−04 0.591 1.164 1.032 1.797 1.046 0.681 223922_x_at MS4A6A 1.29E−03 0.637 1.244 1.049 1.888 1.016 0.656 223982_s_at PNPLA8 4.60E−03 0.741 0.938 0.898 0.752 1.010 1.115 224046_s_at PDE7A 3.79E−05 0.684 0.791 0.805 0.328 1.049 1.434 224374_s_at EMILIN2 1.07E−04 0.669 1.301 1.040 1.950 0.986 0.721 224387_at COMMD5 8.34E−04 0.686 1.226 1.084 2.334 1.017 0.557 224439_x_at RNF7 3.70E−04 0.802 1.172 1.141 2.094 1.035 0.766 224518_s_at ZNF559 3.49E−04 0.599 0.821 0.868 0.304 1.010 1.336 224582_s_at NUCKS1 6.18E−04 0.643 0.788 0.797 0.341 1.091 1.351 224591_at HP1BP3 1.57E−02 0.539 0.918 0.983 0.635 1.030 1.217 224726_at MIB1 4.26E−03 0.747 1.207 1.168 1.867 1.039 0.681 224818_at SORT1 2.51E−04 0.685 1.237 1.104 2.204 1.045 0.682 224917_at MIRN21 1.93E−05 0.675 1.234 1.053 2.016 1.046 0.727 224918_x_at MGST1 3.31E−05 0.685 1.440 1.062 2.755 0.991 0.606 224928_at SETD7 1.18E−05 0.751 1.278 1.138 1.800 1.059 0.666 225059_at AGTRAP 6.73E−04 0.557 1.180 0.958 1.973 1.039 0.736 225064_at RABEP1 6.88E−04 0.628 0.832 0.880 0.556 1.013 1.396 225107_at HNRNPA2B1 7.11E−06 0.635 0.826 0.915 0.563 1.042 1.215 225188_at RAPH1 7.03E−05 0.796 1.838 1.406 5.443 1.009 0.289 225341_at MTERFD3 7.54E−04 0.698 0.696 0.701 0.300 0.984 1.939 225358_at DNAJC19 1.19E−03 0.539 0.880 0.942 0.482 1.030 1.130 225365_at ZDHHC20 4.13E−05 0.678 1.222 1.070 2.054 1.045 0.821 225388_at TSPAN5 4.62E−04 0.635 0.802 0.845 0.455 1.004 1.505 225456_at MED1 2.31E−04 0.604 0.877 0.910 0.673 1.010 1.298 225763_at RCSD1 1.97E−03 0.533 0.903 0.943 0.594 1.002 1.290 225844_at POLE4 5.71E−04 0.741 1.198 1.084 2.300 1.025 0.775 225866_at BXDC1 5.46E−03 0.522 0.859 0.915 0.539 1.041 1.620 225870_s_at TRAPPC5 1.13E−04 0.660 1.227 1.045 2.419 1.028 0.783 226000_at CTTNBP2NL 7.93E−04 0.643 1.186 1.019 2.019 1.021 0.700 226030_at ACADSB 8.00E−04 0.570 0.824 0.909 0.470 1.048 1.384 226042_at EDC3 3.60E−02 0.714 0.943 0.878 0.702 1.022 1.179 226059_at TOMM40L 9.95E−05 0.736 1.339 1.080 2.595 0.989 0.721 226115_at AHCTF1 8.10E−03 0.753 0.860 0.807 0.444 1.018 1.471 226218_at IL7R 2.49E−04 0.575 0.722 0.794 0.292 1.095 1.569 226220_at METTL9 6.45E−04 0.689 1.345 1.047 2.737 1.039 0.606 226323_at CCDC16 9.86E−05 0.720 0.876 0.902 0.646 1.024 1.266 226353_at SPPL2A 2.28E−04 0.724 1.138 1.066 1.559 0.990 0.846 226428_at TNPO2 1.85E−03 0.714 0.900 0.884 0.499 1.029 1.173 226459_at PIK3AP1 4.89E−05 0.645 1.215 1.028 1.907 1.027 0.759 226503_at RIF1 5.07E−04 0.543 0.852 0.923 0.556 1.073 1.256 226683_at SNAG1 2.92E−02 0.801 0.852 0.746 0.533 1.010 2.165 226718_at AMIGO1 6.07E−04 0.582 0.815 0.840 0.596 1.056 1.439 226763_at SESTD1 6.84E−05 0.772 1.419 1.194 3.114 1.143 0.687 226836_at SFT2D1 6.76E−03 0.514 1.075 0.985 1.434 1.028 0.850 227020_at YPEL2 4.34E−03 0.783 1.127 1.119 1.636 1.033 0.684 227114_at RNF214 1.46E−02 0.517 0.882 0.940 0.596 1.069 1.339 227149_at TNRC6C 3.81E−04 0.691 0.815 0.833 0.445 0.963 1.359 227173_s_at BACH2 3.28E−04 0.688 0.711 0.687 0.180 1.047 1.780 227213_at ADAT2 2.84E−04 0.631 0.766 0.791 0.341 0.992 1.567 227374_at EARS2 2.63E−04 0.509 0.831 0.939 0.460 1.065 1.289 227517_s_at GAS5 2.04E−04 0.594 0.772 0.856 0.388 0.978 1.597 227558_at CBX4 6.88E−04 0.747 0.899 0.890 0.737 1.016 1.151 227560_at SFXN2 5.37E−04 0.695 0.867 0.880 0.668 1.020 1.282 227722_at RPS23 1.53E−03 0.676 0.622 0.424 0.046 1.013 2.284 227990_at SLU7 4.23E−03 0.704 0.924 0.864 0.686 1.012 1.142 228012_at MATR3 3.15E−04 0.562 0.825 0.883 0.551 1.039 1.525 228170_at OLIG1 2.17E−04 0.732 1.728 1.255 5.011 1.043 0.474 228176_at EDG3 1.95E−03 0.726 1.499 1.234 3.339 1.054 0.384 228234_at TICAM2 1.04E−03 0.678 1.171 1.052 1.718 1.023 0.753 228370_at SNRPN 3.83E−04 0.564 0.726 0.792 0.175 1.051 1.914 228549_at TMEM63A 7.32E−04 0.634 0.805 0.795 0.468 1.044 1.432 228630_at ZNF84 1.97E−03 0.529 0.820 0.874 0.386 1.038 1.497 228831_s_at GNG7 7.41E−04 0.638 0.766 0.817 0.376 1.045 1.693 229307_at ANKRD28 1.50E−03 0.677 1.612 1.118 4.028 1.170 0.460 229421_s_at FLJ20273 1.26E−03 0.697 1.323 1.092 2.358 1.057 0.669 229509_at MFSD8 8.26E−03 0.515 0.886 0.946 0.635 1.017 1.301 229854_at OBSCN 1.14E−02 0.643 0.899 0.896 0.799 0.945 1.456 229982_at QSER1 1.19E−04 0.792 1.326 1.157 2.120 1.007 0.700 230265_at SEL1L 5.12E−04 0.684 1.324 1.088 2.025 1.000 0.528 230320_at TBRG1 9.67E−04 0.646 0.852 0.871 0.625 1.062 1.199 230408_at PCGF3 1.57E−03 0.564 0.856 0.867 0.610 1.033 1.452 230480_at PIWIL4 3.48E−03 0.666 1.194 1.048 2.206 1.078 0.692 230837_at LOC647500 4.08E−04 0.680 0.884 0.848 0.695 1.000 1.329 230852_at STAC3 5.18E−04 0.715 1.181 1.095 1.877 1.063 0.782 230922_x_at FUNDC2 3.63E−03 0.700 0.907 0.884 0.710 1.012 1.245 231283_at MGAT4A 6.09E−05 0.699 0.797 0.802 0.447 1.040 1.323 231697_s_at TMEM49 2.66E−04 0.642 1.392 0.967 3.233 0.903 0.584 231836_at HKR1 9.87E−04 0.639 0.793 0.856 0.320 1.013 1.840 231843_at DDX55 3.23E−05 0.752 0.842 0.849 0.537 1.038 1.203 231845_at AARS2 2.34E−03 0.512 0.821 0.936 0.522 1.017 1.435 231904_at U2AF1 5.78E−04 0.719 0.841 0.853 0.373 1.027 1.252 231914_at NUDT14 7.59E−04 0.658 1.099 1.035 1.583 1.039 0.800 232636_at SLITRK4 1.16E−04 0.759 1.518 1.326 2.892 1.066 0.414 232851_at FBXO3 7.40E−04 0.739 0.788 0.759 0.479 1.015 1.631 233019_at CNOT7 2.46E−04 0.550 0.839 0.937 0.500 1.007 1.364 233169_at ZNF350 5.49E−04 0.707 0.840 0.797 0.439 1.002 1.347 234013_at TRA@ 2.57E−03 0.504 0.722 0.778 0.326 0.951 1.844 234311_s_at GTPBP10 5.02E−03 0.520 0.864 0.971 0.587 0.998 1.396 234339_s_at GLTSCR2 2.44E−03 0.518 0.794 0.933 0.306 1.071 1.528 234464_s_at EME1 1.02E−03 0.734 1.284 1.100 2.214 1.084 0.605 234733_s_at FANCM 6.29E−04 0.718 0.825 0.809 0.583 0.982 1.456 235024_at PHF17 1.85E−04 0.733 0.866 0.881 0.605 1.075 1.169 235067_at MKLN1 2.85E−02 0.726 0.917 0.855 0.362 1.030 1.170 235200_at ZNF561 2.15E−04 0.645 0.844 0.873 0.595 1.057 1.338 235359_at LRRC33 9.30E−04 0.744 1.257 1.106 1.934 1.061 0.544 235593_at ZEB2 8.32E−07 0.770 1.451 1.201 2.156 1.078 0.690 235610_at ALKBH8 5.70E−04 0.587 0.788 0.831 0.415 1.008 1.893 235623_at ELP2 9.66E−04 0.676 0.894 0.922 0.611 1.003 1.198 235690_at ZNF594 9.02E−04 0.647 0.824 0.835 0.563 1.011 1.635 237504_at INTS10 4.67E−04 0.666 0.855 0.870 0.609 1.038 1.282 238429_at TMEM71 4.30E−02 0.742 0.909 0.840 0.576 1.007 1.358 238513_at PRRG4 9.07E−04 0.646 1.543 1.108 3.989 1.064 0.472 238736_at REV3L 4.11E−04 0.670 0.845 0.863 0.555 1.036 1.477 238823_at FMNL3 1.75E−03 0.766 0.828 0.778 0.419 1.048 1.426 238909_at S100A10 1.40E−03 0.716 1.317 1.138 2.696 0.993 0.663 239108_at MLSTD1 8.51E−04 0.592 1.338 0.964 2.322 1.113 0.516 239897_at BCLAF1 2.75E−03 0.743 0.905 0.883 0.595 1.021 1.191 241704_x_at ZNF320 4.39E−03 0.534 0.865 0.964 0.498 1.053 1.306 241706_at CPNE8 6.88E−05 0.754 1.254 1.136 1.893 1.039 0.686 241731_x_at ZNF440 6.39E−05 0.663 0.849 0.867 0.540 1.014 1.250 242197_x_at CD36 1.29E−05 0.759 2.090 1.487 5.789 1.171 0.357 242561_at IPO9 1.17E−03 0.657 0.836 0.859 0.539 1.038 1.433 242569_at STAM2 6.61E−03 0.749 0.896 0.838 0.573 1.042 1.235 242669_at UFM1 8.10E−04 0.645 0.842 0.864 0.474 1.049 1.248 243982_at KLHL28 3.10E−05 0.674 0.809 0.865 0.606 1.060 1.304 244038_at WDR89 7.97E−05 0.670 0.792 0.838 0.462 1.020 1.498 244654_at MYO1G 2.56E−02 0.746 1.161 1.119 1.826 0.999 0.739 244698_at CDRT4 8.84E−03 0.595 0.930 0.933 0.806 0.994 1.240 36566_at CTNS 1.31E−03 0.747 1.155 1.084 1.550 1.052 0.738 37549_g_at BBS9 3.65E−02 0.698 1.047 1.039 1.189 1.029 0.864 48659_at RP5-1077B9.4 2.84E−04 0.807 1.133 1.098 1.525 1.024 0.836 56829_at NIBP 1.15E−02 0.745 1.078 1.051 1.462 1.015 0.892 64486_at CORO1B 4.79E−04 0.772 1.200 1.098 1.884 1.019 0.736 AFFX-HUMGAPDH/

GAPDH 4.93E−06 0.746 1.148 1.049 1.446 1.027 0.868

indicates data missing or illegible when filed

TABLE 5 Average fold- Average fold- change gene change gene expression expression Affymetrix Probe (NYHA I-II/ (NYHA III-IV/ set ID Gene symbol Control) Control) 1555630_a_at RAB34 1.277 1.306 1555963_x_at B3GNT7 1.206 1.386 1556113_at DKFZp451A211 1.118 1.131 1556283_s_at FGFR1OP2 1.194 1.237 200059_s_at RHOA 1.068 1.068 200650_s_at LDHA 1.099 1.136 200822_x_at TPI1 1.102 1.162 200839_s_at CTSB 1.199 1.330 200932_s_at DCTN2 1.069 1.088 200950_at ARPC1A 1.102 1.148 201098_at COPB2 1.079 1.095 201105_at LGALS1 1.339 1.345 201172_x_at ATP6V0E1 1.075 1.113 201186_at LRPAP1 1.119 1.200 201193_at IDH1 1.192 1.310 201220_x_at CTBP2 1.085 1.160 201234_at ILK 1.137 1.194 201400_at PSMB3 1.106 1.205 201422_at IFI30 1.151 1.234 201426_s_at VIM 1.092 1.123 201453_x_at RHEB 1.084 1.101 201470_at GSTO1 1.171 1.218 201527_at ATP6V1F 1.093 1.110 201536_at DUSP3 1.160 1.303 201554_x_at GYG1 1.140 1.307 201576_s_at GLB1 1.108 1.197 201590_x_at ANXA2 1.259 1.281 201628_s_at RRAGA 1.086 1.104 201900_s_at AKR1A1 1.158 1.170 202068_s_at LDLR 1.352 1.689 202201_at BLVRB 1.196 1.335 202252_at RAB13 1.374 1.393 203127_s_at SPTLC2 1.199 1.247 203305_at F13A1 1.306 1.505 203416_at CD53 1.063 1.085 203844_at VHL 1.066 1.099 203912_s_at DNASE1L1 1.201 1.221 204050_s_at CLTA 1.107 1.108 204099_at SMARCD3 1.240 1.463 204243_at RLF 1.122 1.243 204249_s_at LMO2 1.162 1.210 204675_at SRD5A1 1.321 1.369 205550_s_at BRE 1.057 1.101 206715_at TFEC 1.269 1.400 207113_s_at TNF 1.219 1.277 207543_s_at P4HA1 1.099 1.239 208121_s_at PTPRO 1.456 1.561 208161_s_at ABCC3 1.465 1.654 208659_at CLIC1 1.054 1.129 208771_s_at LTA4H 1.244 1.322 208921_s_at SRI 1.106 1.115 208923_at CYFIP1 1.262 1.343 209099_x_at JAG1 1.201 1.437 209124_at MYD88 1.085 1.117 209191_at TUBB6 1.281 1.407 209218_at SQLE 1.389 1.403 209251_x_at TUBA1C 1.090 1.147 209684_at RIN2 1.244 1.382 210145_at PLA2G4A 1.319 1.507 210156_s_at PCMT1 1.111 1.113 210434_x_at JTB 1.097 1.106 210648_x_at SNX3 1.134 1.165 211047_x_at AP2S1 1.136 1.149 211058_x_at TUBA1B 1.059 1.095 211684_s_at DYNC1I2 1.182 1.186 212334_at GNS 1.118 1.152 212658_at LHFPL2 1.348 1.569 212663_at FKBP15 1.119 1.147 212820_at DMXL2 1.151 1.249 213335_s_at ST3GAL6 1.124 1.186 213494_s_at YY1 1.199 1.279 214430_at GLA 1.096 1.180 214511_x_at FCGR1B 1.560 1.889 214629_x_at RTN4 1.071 1.125 215049_x_at CD163 1.279 1.485 215273_s_at TADA3L 1.061 1.113 216484_x_at HDGF 1.083 1.098 216950_s_at FCGR1A 1.641 1.987 217383_at PGK1 1.184 1.286 217769_s_at POMP 1.090 1.107 218091_at HRB 1.128 1.206 218206_x_at SCAND1 1.077 1.126 218351_at COMMD8 1.103 1.119 218627_at DRAM 1.183 1.344 218718_at PDGFC 1.412 1.416 218732_at PTRH2 1.165 1.222 218845_at DUSP22 1.166 1.174 219316_s_at FLVCR2 1.297 1.382 219358_s_at CENTA2 1.234 1.294 219952_s_at MCOLN1 1.155 1.252 220146_at TLR7 1.404 1.417 220160_s_at KPTN 1.151 1.194 220605_s_at SIRT2 1.076 1.127 220865_s_at PDSS1 1.182 1.357 220974_x_at SFXN3 1.190 1.210 221449_s_at ITFG1 1.092 1.155 221647_s_at RIC8A 1.093 1.097 221731_x_at VCAN 1.129 1.267 221841_s_at KLF4 1.403 1.476 221960_s_at RAB2A 1.388 1.490 222217_s_at SLC27A3 1.268 1.314 222231_s_at LRRC59 1.135 1.150 222651_s_at TRPS1 1.159 1.249 222670_s_at MAFB 1.344 1.369 222753_s_at SPCS3 1.120 1.206 222774_s_at NETO2 1.242 1.297 222980_at RAB10 1.087 1.107 223064_at RNF181 1.090 1.109 223158_s_at NEK6 1.253 1.254 223465_at COL4A3BP 1.133 1.234 223801_s_at APOL4 1.094 1.164 224387_at COMMD5 1.139 1.226 224818_at SORT1 1.165 1.237 224917_at MIRN21 1.158 1.234 224918_x_at MGST1 1.253 1.440 224928_at SETD7 1.195 1.278 225188_at RAPH1 1.812 1.838 225365_at ZDHHC20 1.118 1.222 225844_at POLE4 1.160 1.198 225870_s_at TRAPPC5 1.117 1.227 226000_at CTTNBP2NL 1.117 1.186 226059_at TOMM40L 1.191 1.339 226220_at METTL9 1.233 1.345 226353_at SPPL2A 1.122 1.138 226459_at PIK3AP1 1.159 1.215 226763_at SESTD1 1.324 1.419 228170_at OLIG1 1.514 1.728 228176_at EDG3 1.399 1.499 228234_at TICAM2 1.149 1.171 229307_at ANKRD28 1.410 1.612 229421_s_at FLJ20273 1.213 1.323 230265_at SEL1L 1.189 1.324 230852_at STAC3 1.152 1.181 231914_at NUDT14 1.085 1.099 232636_at SLITRK4 1.492 1.518 234464_s_at EME1 1.262 1.284 235359_at LRRC33 1.232 1.257 235593_at ZEB2 1.282 1.451 238909_at S100A10 1.255 1.317 241706_at CPNE8 1.194 1.254 242197_x_at CD36 1.871 2.090 AFFX- GAPDH 1.103 1.148 HUMGAPDH/ M33197_3_at

TABLE 6 Average fold- Average fold- change gene change gene expression expression Affymetrix Probe (NYHA I-II/ (NYHA III-IV/ set ID Gene symbol Control) Control) 1558277_at ZNF740 1.326 1.175 200713_s_at MAPRE1 1.106 1.073 200829_x_at ZNF207 1.147 1.125 201198_s_at PSMD1 1.138 1.114 202185_at PLOD3 1.135 1.101 202428_x_at DBI 1.174 1.118 202461_at EIF2B2 1.195 1.117 202522_at PITPNB 1.094 1.063 202944_at NAGA 1.226 1.219 203534_at LSM1 1.149 1.147 203880_at COX17 1.167 1.136 206170_at ADRB2 1.459 1.320 208680_at PRDX1 1.224 1.215 208805_at PSMA6 1.145 1.120 209040_s_at PSMB8 1.135 1.115 209892_at FUT4 1.303 1.270 210644_s_at LAIR1 1.341 1.278 211383_s_at WDR37 1.118 1.065 211729_x_at BLVRA 1.250 1.241 212543_at AIM1 1.130 1.090 214853_s_at SHC1 1.131 1.124 214953_s_at APP 1.359 1.315 218143_s_at SCAMP2 1.158 1.111 219507_at RSRC1 1.338 1.214 220750_s_at LEPRE1 1.169 1.135 224439_x_at RNF7 1.175 1.172 224726_at MIB1 1.228 1.207 227020_at YPEL2 1.145 1.127 229982_at QSER1 1.379 1.326 230480_at PIWIL4 1.265 1.194 244654_at MYO1G 1.227 1.161 36566_at CTNS 1.178 1.155 37549_g_at BBS9 1.075 1.047 48659_at RP5-1077B9.4 1.159 1.133 56829_at NIBP 1.099 1.078 64486_at CORO1B 1.210 1.200

TABLE 7 Average fold- Average fold- change gene change gene expression expression Affymetrix Probe (NYHA I-II/ (NYHA III-IV/ set ID Gene symbol Control) Control) 1552630_a_at SRCAP 0.831 0.815 1554149_at CLDND1 0.907 0.856 1554606_at CCDC100 0.860 0.760 1557066_at LUC7L 0.873 0.776 1558755_x_at ZNF763 0.816 0.753 1564962_at ZNF92 0.799 0.748 1568815_a_at DDX50 0.836 0.762 200672_x_at SPTBN1 0.893 0.773 201075_s_at SMARCC1 0.874 0.864 201556_s_at VAMP2 0.810 0.801 202249_s_at WDR42A 0.925 0.890 202523_s_at SPOCK2 0.834 0.674 202623_at EAPP 0.917 0.896 202652_at APBB1 0.862 0.753 202724_s_at FOXO1 0.881 0.847 202778_s_at ZMYM2 0.907 0.899 202928_s_at PHF1 0.852 0.818 203137_at WTAP 0.929 0.889 203413_at NELL2 0.799 0.608 203939_at NT5E 0.802 0.743 204291_at ZNF518 0.924 0.872 204401_at KCNN4 0.828 0.813 204617_s_at ACD 0.895 0.871 204645_at CCNT2 0.886 0.863 205235_s_at MPHOSPH1 0.905 0.883 205254_x_at TCF7 0.862 0.666 205256_at ZBTB39 0.935 0.887 206182_at ZNF134 0.925 0.853 206542_s_at SMARCA2 0.900 0.873 206968_s_at NFRKB 0.919 0.850 207078_at MED6 0.887 0.797 207513_s_at ZNF189 0.898 0.897 208269_s_at ADAM28 0.859 0.840 208946_s_at BECN1 0.938 0.935 209236_at SLC23A2 0.901 0.826 209675_s_at HNRPUL1 0.870 0.843 211185_s_at SF3B1 0.943 0.918 211323_s_at ITPR1 0.873 0.798 211856_x_at CD28 0.839 0.654 211946_s_at BAT2D1 0.933 0.910 212030_at RBM25 0.897 0.818 212132_at LSM14A 0.925 0.881 212455_at YTHDC1 0.917 0.878 212997_s_at TLK2 0.919 0.915 213218_at ZNF187 0.857 0.816 213459_at RPL37A 0.848 0.822 214820_at BRWD1 0.909 0.837 215293_s_at FRAG1 0.882 0.864 215567_at FGF1 0.863 0.766 217987_at ASNSD1 0.810 0.774 218012_at TSPYL2 0.894 0.792 218040_at PRPF38B 0.936 0.898 218127_at NFYB 0.940 0.872 218499_at RP6-213H19.1 0.934 0.878 219826_at ZNF419 0.869 0.733 221428_s_at TBL1XR1 0.892 0.851 221580_s_at JOSD3 0.930 0.859 221601_s_at FAIM3 0.865 0.703 221868_at PAIP2B 0.823 0.764 222700_at ARL6IP2 0.906 0.850 224046_s_at PDE7A 0.885 0.791 224518_s_at ZNF559 0.890 0.821 225341_at MTERFD3 0.740 0.696 225388_at TSPAN5 0.865 0.802 225456_at MED1 0.934 0.877 226323_at CCDC16 0.908 0.876 227149_at TNRC6C 0.860 0.815 227173_s_at BACH2 0.804 0.711 227558_at CBX4 0.916 0.899 227560_at SFXN2 0.910 0.867 227722_at RPS23 0.655 0.622 228549_at TMEM63A 0.893 0.805 228831_s_at GNG7 0.842 0.766 230837_at LOC647500 0.901 0.884 231283_at MGAT4A 0.873 0.797 231843_at DDX55 0.874 0.842 231904_at U2AF1 0.861 0.841 232851_at FBXO3 0.813 0.788 233169_at ZNF350 0.849 0.840 234733_s_at FANCM 0.879 0.825 235024_at PHF17 0.893 0.866 235200_at ZNF561 0.904 0.844 235623_at ELP2 0.922 0.894 237504_at INTS10 0.901 0.855 238736_at REV3L 0.880 0.845 239897_at BCLAF1 0.905 0.905 241731_x_at ZNF440 0.919 0.849 242561_at IPO9 0.889 0.836 243982_at KLHL28 0.870 0.809 244038_at WDR89 0.897 0.792

TABLE 8 Average fold- Average fold- change gene change gene expression expression Affymetrix Probe (NYHA I-II/ (NYHA III-IV/ set ID Gene symbol Control) Control) 1556864_at TECT1 0.849 0.852 1561146_at VPS35 0.789 0.790 201357_s_at SF3A1 0.847 0.898 201363_s_at IVNS1ABP 0.851 0.856 203003_at MEF2D 0.835 0.897 204801_s_at DHRS12 0.757 0.782 207164_s_at ZNF238 0.845 0.870 209269_s_at SYK 0.823 0.893 210875_s_at ZEB1 0.768 0.783 211506_s_at IL8 0.495 0.710 213877_x_at TCEB2 0.912 0.930 214683_s_at CLK1 0.890 0.905 214931_s_at SRPK2 0.853 0.882 215997_s_at CUL4B 0.848 0.902 222574_s_at DHX40 0.867 0.871 223444_at SENP7 0.871 0.882 223982_s_at PNPLA8 0.922 0.938 226042_at EDC3 0.905 0.943 226115_at AHCTF1 0.815 0.860 226428_at TNPO2 0.898 0.900 226683_at SNAG1 0.784 0.852 227990_at SLU7 0.895 0.924 230922_x_at FUNDC2 0.906 0.907 235067_at MKLN1 0.872 0.917 238429_at TMEM71 0.847 0.909 238823_at FMNL3 0.827 0.828 242569_at STAM2 0.863 0.896 

1. A method of determining a severity of heart failure in a human test subject, the method comprising, for each gene of a set of one or more of the genes listed in Tables 3, 4, 5, 6, 7 and 8: a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating a test data; b) providing a control data representing levels of RNA encoded by the gene in blood of human control subjects having a categorized severity of heart failure; and c) comparing the levels of steps a) and b) to thereby determine at least one value indicating whether the test data corresponds to the control data; wherein an indication by the at least one value, for each gene of the set, that the test data corresponds to the control data indicates that the test subject has the categorized severity of heart failure.
 2. The method of claim 1, wherein the categorized severity is compensated heart failure, optionally NYHA I/NYHA II heart failure, or decompensated heart failure, optionally NYHA III/NYHA IV heart failure.
 3. The method of claim 1, wherein the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by the gene in blood of subjects not having heart failure.
 4. The method of claim 1, further comprising determining levels of RNA encoded by the gene in blood of a population of human subjects having the categorized severity of heart failure, thereby providing the control data.
 5. The method of claim 1, wherein step c) is effected by causing a suitably programmed computer to compare the test data to the control data to thereby generate the at least one value indicating whether the test data corresponds to the control data.
 6. A method of monitoring the progression of heart failure in a human subject, the method comprising, for each gene of a set of one or more of the genes listed in Table 5: a) determining a level of RNA encoded by the gene in blood of the subject at a first time point; b) determining a level of RNA encoded by the gene in blood of the subject at a second time point, wherein the second time point is later than the first time point; c) comparing the levels of steps a) and b) to thereby determine at least one value indicating whether the level at the second time point is higher than the level at the first time point; wherein an indication by the at least one value, for each gene of the set, that the level at the second time point is higher than the level at the first time point indicates a progression of heart failure.
 7. A method of monitoring the progression of heart failure in a human subject, the method comprising, for each gene of a set of one or more of the genes listed in Table 7: a) determining a level of RNA encoded by the gene in blood of the subject at a first time point; b) determining a level of RNA encoded by the gene in blood of the subject at a second time point, wherein the second time point is later than the first time point; c) comparing the levels of steps a) and b) to thereby determine at least one value indicating whether the level at the second time point is lower than the level at the first time point; wherein an indication by the at least one value, for each gene of the set, that the level at the second time point is lower than the level at the first time point indicates a progression of heart failure.
 8. The method of claim 6 or 7, wherein the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by the gene in blood of subjects not having heart failure.
 9. The method of claim 6, wherein step c) is effected by causing a suitably programmed computer to compare a data representing the level at the first time point to a data representing the level at the second time point to thereby determine the at least one value indicating whether the level at the second time point is higher than the level at the first time point.
 10. The method of claim 7, wherein step c) is effected by causing a suitably programmed computer to compare a data representing the level at the first time point to a data representing the level at the second time point to thereby determine the at least one value indicating whether the level at the second time point is lower than the level at the first time point.
 11. A kit comprising packaging and containing, for each gene of a set of two or more of the genes listed in Table 1, a primer set capable of generating an amplification product of DNA complementary to RNA encoded, in a human subject, only by the gene.
 12. The kit of claim 11, further comprising for a control gene, a primer set capable of generating an amplification product of DNA complementary to RNA, wherein the RNA is encoded, in the human genome, only by the control gene.
 13. The kit of claim 11 or 12, further comprising a component selected from the group consisting of a thermostable polymerase, a reverse transcriptase, deoxynucleotide triphosphates, nucleotide triphosphates and enzyme buffer.
 14. The kit of claim 11, 12 or 13, further comprising at least one labeled probe capable of selectively hybridizing to either a sense or an antisense strand of the amplification product.
 15. The kit of claim 11, 12, 13 or 14, further comprising a computer-readable medium having instructions stored thereon that are operable when executed by a computer for comparing a test data representing a level of RNA encoded by the gene in blood of a human test subject to a control data representing levels of RNA encoded by the gene in blood of human control subjects having a categorized severity of heart failure to thereby determine at least one value indicating whether the test data corresponds to the control data, wherein an indication by the at least one value that the test data corresponds to the control data classifies the test subject as having the categorized severity of heart failure.
 16. A method of classifying a human test subject as having decompensated heart failure, optionally NYHA class III-IV heart failure, the method comprising: a) determining a level of RNA encoded by each gene of a set of one or more of the genes listed in Tables 5 and 6 in blood of the test subject, thereby generating a test data; b) providing a control data representing a level of RNA encoded by the gene in blood of human control subjects not having heart failure; and c) comparing the test data to the control data to thereby determine at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having heart failure, wherein an indication by the at least one value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having heart failure classifies the test subject as having decompensated heart failure.
 17. The method of claim 16 wherein the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by a gene in blood of a subject not having heart failure.
 18. The method of claim 16, further comprising determining levels of RNA encoded by the gene in blood of human subjects not having decompensated heart failure, thereby providing the control data.
 19. The method of claim 16, wherein step c) is effected by causing a suitably programmed computer to compare a test data representing the level of RNA encoded by the gene in blood of the test subject to a control data representing the level of RNA encoded by the gene in blood of human control subjects not having heart failure to thereby determine the at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having heart failure.
 20. A method of classifying a human test subject as having decompensated heart failure, optionally NYHA class III-IV heart failure, the method comprising: a) determining a level of RNA encoded by each gene of a set of one or more of the genes listed in Tables 7 and 8 in blood of the test subject, thereby generating a test data; b) providing a control data representing a level of RNA encoded by the gene in blood of human control subjects not having heart failure; and c) comparing the test data to the control data to thereby determine at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having heart failure, wherein an indication by the at least one value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having heart failure classifies the test subject as having decompensated heart failure.
 21. The method of claim 20 wherein the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by the gene in blood of subjects not having heart failure.
 22. The method of claim 20, further comprising determining levels of RNA encoded by the gene in blood of human subjects not having decompensated heart failure, thereby providing the control data.
 23. The method of claim 20, wherein step c) is effected by causing a suitably programmed computer to compare a test data representing the level of RNA encoded by the gene in blood of the test subject to a control data representing a level of RNA encoded by the gene in blood of human control subjects not having heart failure to thereby determine the at least one value indicating whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having heart failure. 